Instructions to use LEAP-LAB-KUS/jevkt-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LEAP-LAB-KUS/jevkt-checkpoints with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
pod backup 2026-11-07: e33 (0-66)
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- e33/S1-E33-M10-rt-n16k-a100-syn/DONE +1 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter/README.md +206 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/calibration.json +29 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/head.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/judge_config.json +164 -0
- e33/S1-E33-M10-rt-n16k-a100-syn/train_log.jsonl +57 -0
- e33/S1-E33-M10-rt-n16k-syn/DONE +1 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/README.md +206 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/calibration.json +29 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/head.safetensors +3 -0
- e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/judge_config.json +164 -0
- e33/S1-E33-M10-rt-n16k-syn/train_log.jsonl +57 -0
- e33/S1-E33-M20P40-n16k-a100-syn/DONE +1 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/README.md +206 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/calibration.json +29 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/head.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/judge_config.json +164 -0
- e33/S1-E33-M20P40-n16k-a100-syn/train_log.jsonl +57 -0
- e33/S1-E33-M20P40-n16k-syn/DONE +1 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/README.md +206 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/calibration.json +29 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/head.safetensors +3 -0
- e33/S1-E33-M20P40-n16k-syn/ckpt-16000/judge_config.json +164 -0
- e33/S1-E33-M20P40-n16k-syn/train_log.jsonl +57 -0
- e33/S1-E33-M40P40-n16k-a100-syn/DONE +1 -0
- e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/README.md +206 -0
- e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
e33/S1-E33-M10-rt-n16k-a100-syn/DONE
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| 1 |
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---
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| 2 |
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base_model: /workspace/jev_kt/models/hf/JEV-9B
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library_name: peft
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tags:
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- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
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- lora
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- transformers
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| 8 |
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---
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| 9 |
+
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| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
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| 19 |
+
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| 20 |
+
<!-- Provide a longer summary of what this model is. -->
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| 21 |
+
|
| 22 |
+
|
| 23 |
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| 24 |
+
- **Developed by:** [More Information Needed]
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| 25 |
+
- **Funded by [optional]:** [More Information Needed]
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| 26 |
+
- **Shared by [optional]:** [More Information Needed]
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| 27 |
+
- **Model type:** [More Information Needed]
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| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
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| 29 |
+
- **License:** [More Information Needed]
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| 30 |
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- **Finetuned from model [optional]:** [More Information Needed]
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| 31 |
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|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
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| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
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| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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| 43 |
+
|
| 44 |
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### Direct Use
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| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
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### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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| 53 |
+
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| 54 |
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[More Information Needed]
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| 55 |
+
|
| 56 |
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### Out-of-Scope Use
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| 57 |
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| 58 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 59 |
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| 60 |
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[More Information Needed]
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| 61 |
+
|
| 62 |
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## Bias, Risks, and Limitations
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| 63 |
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| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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| 65 |
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| 66 |
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[More Information Needed]
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| 67 |
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| 68 |
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### Recommendations
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| 69 |
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| 70 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 71 |
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| 72 |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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| 73 |
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| 74 |
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## How to Get Started with the Model
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| 75 |
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| 76 |
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Use the code below to get started with the model.
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| 77 |
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| 78 |
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[More Information Needed]
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## Training Details
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| 81 |
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### Training Data
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| 83 |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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| 89 |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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| 98 |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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| 101 |
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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| 106 |
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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| 112 |
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#### Testing Data
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| 114 |
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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| 118 |
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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| 124 |
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#### Metrics
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| 126 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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| 132 |
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[More Information Needed]
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| 134 |
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#### Summary
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| 136 |
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| 137 |
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## Model Examination [optional]
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| 140 |
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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| 144 |
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## Environmental Impact
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| 146 |
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| 147 |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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| 148 |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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| 151 |
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- **Hardware Type:** [More Information Needed]
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| 152 |
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- **Hours used:** [More Information Needed]
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| 153 |
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- **Cloud Provider:** [More Information Needed]
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| 154 |
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- **Compute Region:** [More Information Needed]
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| 155 |
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- **Carbon Emitted:** [More Information Needed]
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| 156 |
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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| 164 |
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[More Information Needed]
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| 166 |
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| 167 |
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#### Hardware
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| 168 |
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[More Information Needed]
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#### Software
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| 172 |
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[More Information Needed]
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| 174 |
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## Citation [optional]
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| 176 |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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| 178 |
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**BibTeX:**
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[More Information Needed]
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**APA:**
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| 184 |
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[More Information Needed]
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| 186 |
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| 187 |
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## Glossary [optional]
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| 188 |
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| 189 |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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| 190 |
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[More Information Needed]
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## More Information [optional]
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| 194 |
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[More Information Needed]
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## Model Card Authors [optional]
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| 198 |
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[More Information Needed]
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## Model Card Contact
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| 202 |
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[More Information Needed]
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| 204 |
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### Framework versions
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| 205 |
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| 206 |
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- PEFT 0.21.2
|
e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json
ADDED
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@@ -0,0 +1,57 @@
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e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/calibration.json
ADDED
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| 29 |
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|
e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000/head.safetensors
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ADDED
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|
| 1 |
+
{
|
| 2 |
+
"base_model_path": "/root/models/Qwen3.5-9B",
|
| 3 |
+
"hidden_size": 4096,
|
| 4 |
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| 5 |
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"num_slots": 24,
|
| 6 |
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|
| 7 |
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| 8 |
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0,
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| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
+
2,
|
| 13 |
+
8
|
| 14 |
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],
|
| 15 |
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"choice": [
|
| 16 |
+
8,
|
| 17 |
+
24
|
| 18 |
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]
|
| 19 |
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},
|
| 20 |
+
"verbalizers": [
|
| 21 |
+
"false",
|
| 22 |
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"true",
|
| 23 |
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"0",
|
| 24 |
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|
| 25 |
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"2",
|
| 26 |
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"3",
|
| 27 |
+
"4",
|
| 28 |
+
"5",
|
| 29 |
+
"A",
|
| 30 |
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"B",
|
| 31 |
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"C",
|
| 32 |
+
"D",
|
| 33 |
+
"E",
|
| 34 |
+
"F",
|
| 35 |
+
"G",
|
| 36 |
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"H",
|
| 37 |
+
"I",
|
| 38 |
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"J",
|
| 39 |
+
"K",
|
| 40 |
+
"L",
|
| 41 |
+
"M",
|
| 42 |
+
"N",
|
| 43 |
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"O",
|
| 44 |
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"P"
|
| 45 |
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],
|
| 46 |
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"template_version": "bare-v1"
|
| 47 |
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|
| 48 |
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"verbalizer_ids": [
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| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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| 53 |
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| 54 |
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| 55 |
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42,
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43,
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| 69 |
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| 70 |
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45,
|
| 71 |
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46,
|
| 72 |
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47
|
| 73 |
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],
|
| 74 |
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"kinds": [
|
| 75 |
+
"noul",
|
| 76 |
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"choice",
|
| 77 |
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"score"
|
| 78 |
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],
|
| 79 |
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"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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"model_version": "0.8.0",
|
| 81 |
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"lm_head_included": true,
|
| 82 |
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"weights_mode": "unmerged",
|
| 83 |
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"adapter_subfolder": "adapter",
|
| 84 |
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"lora": {
|
| 85 |
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"r": 16,
|
| 86 |
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"lora_alpha": 32,
|
| 87 |
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"lora_dropout": 0.05,
|
| 88 |
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"target_modules": [
|
| 89 |
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"down_proj",
|
| 90 |
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"gate_proj",
|
| 91 |
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"in_proj_qkv",
|
| 92 |
+
"in_proj_z",
|
| 93 |
+
"k_proj",
|
| 94 |
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"o_proj",
|
| 95 |
+
"out_proj",
|
| 96 |
+
"q_proj",
|
| 97 |
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"up_proj",
|
| 98 |
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"v_proj"
|
| 99 |
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]
|
| 100 |
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},
|
| 101 |
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"trained_stage": "e16",
|
| 102 |
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"source_checkpoint": "models/e33/S1-E33-M10-rt-n16k-a100-syn/ckpt-16000",
|
| 103 |
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"softcap": null,
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| 104 |
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"e16": {
|
| 105 |
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"data": "data/e33/E33-M10-rt-n16k-a100",
|
| 106 |
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"data_manifest": {
|
| 107 |
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| 110 |
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| 111 |
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| 112 |
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| 113 |
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| 114 |
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| 115 |
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|
| 117 |
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|
| 118 |
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|
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|
| 121 |
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|
| 122 |
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|
| 123 |
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| 124 |
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| 126 |
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"max_len": 3072,
|
| 127 |
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|
| 128 |
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"total_rows": 16000,
|
| 129 |
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|
| 130 |
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"r": 16,
|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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"trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3",
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| 135 |
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"event": "ckpt",
|
| 136 |
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"tag": "ckpt-16000",
|
| 137 |
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|
| 138 |
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|
| 139 |
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|
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|
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|
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|
| 143 |
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|
| 144 |
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|
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| 148 |
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| 149 |
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| 150 |
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| 152 |
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| 153 |
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"noul_acc": 0.699,
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| 154 |
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|
| 155 |
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|
| 156 |
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| 159 |
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| 161 |
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| 162 |
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| 163 |
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|
| 164 |
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}
|
e33/S1-E33-M10-rt-n16k-a100-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
+
{"time": "09:20:27", "event": "start", "data": "data/e33/E33-M10-rt-n16k-a100", "data_manifest": {"arm": "E33-M10-rt-n16k-a100", "name": null, "train_sha256": "e0cc7b84a6deb613bff644587c8fc7dda043c2c3266043dc7df4c0c79180428f", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 77.06579637527466}
|
| 2 |
+
{"time": "09:24:08", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 891.0474855226341, "loss": 0.6033337190747261, "entropy": 0.6253835633397102, "sharp": 0.15371828898787498}
|
| 3 |
+
{"time": "09:27:49", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 898.7678657186418, "loss": 0.7838748916983604, "entropy": 0.6202669739723206, "sharp": 0.17797065526247025}
|
| 4 |
+
{"time": "09:31:29", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 900.5382753446562, "loss": 0.6850737277418375, "entropy": 0.6641247570514679, "sharp": 0.10811960324645042}
|
| 5 |
+
{"time": "09:35:01", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 900.3117851157423, "loss": 0.6847868859767914, "entropy": 0.6819761171936989, "sharp": 0.05960580799728632}
|
| 6 |
+
{"time": "09:38:33", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 900.4366446851287, "loss": 0.5863783843815327, "entropy": 0.575633630156517, "sharp": 0.19002662599086761}
|
| 7 |
+
{"time": "09:42:12", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 903.3374492922703, "loss": 0.5031997989863157, "entropy": 0.6125824078917503, "sharp": 0.1816745474934578}
|
| 8 |
+
{"time": "09:45:44", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 903.7665703758253, "loss": 0.606873907148838, "entropy": 0.6636044085025787, "sharp": 0.10620175953954458}
|
| 9 |
+
{"time": "09:49:21", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 903.3837596631068, "loss": 0.67482590675354, "entropy": 0.6118676699697971, "sharp": 0.15935452934354544}
|
| 10 |
+
{"time": "09:52:53", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 903.3855343113702, "loss": 0.6431846879422665, "entropy": 0.6385258324444294, "sharp": 0.1421925025060773}
|
| 11 |
+
{"time": "09:56:36", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 903.9834459122642, "loss": 0.6846701428294182, "entropy": 0.6390752457082272, "sharp": 0.14440846256911755}
|
| 12 |
+
{"time": "09:58:00", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.6084082722663879, "noul_T": 0.6766352911501362, "noul_auc": 0.7320551551872544, "noul_acc": 0.702, "noul_f1": 0.764612954186414, "noul_nll": 0.6007609467208386, "noul_ece": 0.10155431270599366, "noul_brier": 0.20541022797599395, "noul_sharp": 0.13225561380386353, "entropy": 0.6460034251213074}
|
| 13 |
+
{"time": "10:01:37", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 873.0366049535218, "loss": 0.6482396014034748, "entropy": 0.6171336583793163, "sharp": 0.17463437281548977}
|
| 14 |
+
{"time": "10:05:05", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 875.1641802576061, "loss": 0.5996145531535149, "entropy": 0.6567100770771503, "sharp": 0.11905446369200945}
|
| 15 |
+
{"time": "10:08:38", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 876.9032903879504, "loss": 0.6384086310863495, "entropy": 0.6788572743535042, "sharp": 0.06982394959777594}
|
| 16 |
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{"time": "10:12:14", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 878.9804242819296, "loss": 0.5768000446259975, "entropy": 0.6693370379507542, "sharp": 0.09189106337726116}
|
| 17 |
+
{"time": "10:15:49", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 880.4348184722512, "loss": 0.6017400855198503, "entropy": 0.5698162391781807, "sharp": 0.21178777143359184}
|
| 18 |
+
{"time": "10:19:27", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 881.5823790589051, "loss": 0.6542864292860031, "entropy": 0.5234885523095727, "sharp": 0.2540337862446904}
|
| 19 |
+
{"time": "10:23:00", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 882.7998236958621, "loss": 0.5910687409341335, "entropy": 0.6635227352380753, "sharp": 0.10423886124044657}
|
| 20 |
+
{"time": "10:26:37", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 883.9654856469632, "loss": 0.5948001351207495, "entropy": 0.6536477170884609, "sharp": 0.11783802974969149}
|
| 21 |
+
{"time": "10:30:13", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 884.6143325550358, "loss": 0.6801256858743727, "entropy": 0.6189041864126921, "sharp": 0.16625779680907726}
|
| 22 |
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{"time": "10:33:53", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 885.7659601500735, "loss": 0.6023488454520702, "entropy": 0.6618353426456451, "sharp": 0.10348301753401756}
|
| 23 |
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{"time": "10:35:16", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.613629937171936, "noul_T": 0.8413533877688976, "noul_auc": 0.7025704207523923, "noul_acc": 0.674, "noul_f1": 0.7634252539912917, "noul_nll": 0.6114704060256482, "noul_ece": 0.06213674157857896, "noul_brier": 0.21065328342820616, "noul_sharp": 0.14712855219841003, "entropy": 0.6329501271247864}
|
| 24 |
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{"time": "10:38:58", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 871.2871728674021, "loss": 0.63688157312572, "entropy": 0.6147606391459703, "sharp": 0.17704907432198524}
|
| 25 |
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{"time": "10:42:32", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 872.5228054587427, "loss": 0.6519083455204964, "entropy": 0.6725699678063393, "sharp": 0.08100294321775436}
|
| 26 |
+
{"time": "10:46:13", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 873.2950804448907, "loss": 0.6356181167066097, "entropy": 0.6462880596518517, "sharp": 0.12306220084428787}
|
| 27 |
+
{"time": "10:49:53", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 874.3815137635282, "loss": 0.6321443058550358, "entropy": 0.652955025434494, "sharp": 0.11930426955223083}
|
| 28 |
+
{"time": "10:53:33", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 875.7611935040712, "loss": 0.6394157260656357, "entropy": 0.6025685258209705, "sharp": 0.1883924026042223}
|
| 29 |
+
{"time": "10:57:14", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 876.6742822955374, "loss": 0.6191202476620674, "entropy": 0.6671462059020996, "sharp": 0.09179499931633472}
|
| 30 |
+
{"time": "11:00:47", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 877.4646161094252, "loss": 0.6553642265498638, "entropy": 0.6592379845678806, "sharp": 0.1110451053828001}
|
| 31 |
+
{"time": "11:04:26", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 877.971221797522, "loss": 0.6024574413895607, "entropy": 0.6117802187800407, "sharp": 0.17410529032349586}
|
| 32 |
+
{"time": "11:07:55", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 878.6396164404216, "loss": 0.6674257572740316, "entropy": 0.6629147864878178, "sharp": 0.10723049286752939}
|
| 33 |
+
{"time": "11:11:39", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 879.5878966609004, "loss": 0.6327837016433477, "entropy": 0.6372476555407047, "sharp": 0.14154105819761753}
|
| 34 |
+
{"time": "11:13:02", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5927555561065674, "noul_T": 0.9140837438194751, "noul_auc": 0.7317513628461967, "noul_acc": 0.666, "noul_f1": 0.7727891156462585, "noul_nll": 0.5982471793740988, "noul_ece": 0.07837080037593842, "noul_brier": 0.20586142497615276, "noul_sharp": 0.17416174709796906, "entropy": 0.6058613657951355}
|
| 35 |
+
{"time": "11:16:37", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 869.6137309110122, "loss": 0.6072483845055103, "entropy": 0.5658436417579651, "sharp": 0.20860496163368225}
|
| 36 |
+
{"time": "11:20:14", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 870.7963165762047, "loss": 0.6785305291414261, "entropy": 0.6227179393172264, "sharp": 0.1529350159689784}
|
| 37 |
+
{"time": "11:23:52", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 871.4461092863057, "loss": 0.6080680526793003, "entropy": 0.640902929008007, "sharp": 0.1289919689297676}
|
| 38 |
+
{"time": "11:27:28", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 872.4537510502763, "loss": 0.6423982172273099, "entropy": 0.6232390608638525, "sharp": 0.1561298780143261}
|
| 39 |
+
{"time": "11:31:08", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 873.4323797092313, "loss": 0.65891507640481, "entropy": 0.6288746707141399, "sharp": 0.14588055666536093}
|
| 40 |
+
{"time": "11:34:44", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 874.1338999630548, "loss": 0.6176988501101732, "entropy": 0.6252961456775665, "sharp": 0.13359309546649456}
|
| 41 |
+
{"time": "11:38:28", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 874.6831089882023, "loss": 0.744150634855032, "entropy": 0.6299264468252659, "sharp": 0.1376659180969}
|
| 42 |
+
{"time": "11:41:58", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 875.1158409723324, "loss": 0.5802575796842575, "entropy": 0.6352507062256336, "sharp": 0.14148460514843464}
|
| 43 |
+
{"time": "11:45:39", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 875.5994456569073, "loss": 0.7059405953623354, "entropy": 0.6364332772791386, "sharp": 0.12399807758629322}
|
| 44 |
+
{"time": "11:49:25", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 876.3615689884818, "loss": 0.6372781246900558, "entropy": 0.6148921549320221, "sharp": 0.15839910320937634}
|
| 45 |
+
{"time": "11:50:48", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5831224322319031, "noul_T": 0.973220551345713, "noul_auc": 0.7322745607669069, "noul_acc": 0.71, "noul_f1": 0.7792998477929984, "noul_nll": 0.5908164388295263, "noul_ece": 0.06788681399822236, "noul_brier": 0.20089749663804382, "noul_sharp": 0.18074163794517517, "entropy": 0.5872051119804382}
|
| 46 |
+
{"time": "11:54:30", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 869.1485172518481, "loss": 0.5657886452972889, "entropy": 0.6486924085766077, "sharp": 0.11286498792469501}
|
| 47 |
+
{"time": "11:58:14", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 870.0233991919794, "loss": 0.5447256825864315, "entropy": 0.6085926666855812, "sharp": 0.16909427661448717}
|
| 48 |
+
{"time": "12:02:00", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 870.6947731484165, "loss": 0.6258899383246899, "entropy": 0.6019481364637613, "sharp": 0.16560775693506002}
|
| 49 |
+
{"time": "12:05:35", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 871.4700596618806, "loss": 0.6144727133214474, "entropy": 0.6315025687217712, "sharp": 0.1404762426391244}
|
| 50 |
+
{"time": "12:09:21", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 872.1645453687298, "loss": 0.5760183185338974, "entropy": 0.656073272228241, "sharp": 0.10922098997980356}
|
| 51 |
+
{"time": "12:12:58", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 872.7241558853473, "loss": 0.6531402003020048, "entropy": 0.6523221842944622, "sharp": 0.12087107170373201}
|
| 52 |
+
{"time": "12:16:37", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 873.3651392286066, "loss": 0.6043087020516396, "entropy": 0.6481751687824726, "sharp": 0.1281145429238677}
|
| 53 |
+
{"time": "12:20:16", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 873.6749996879207, "loss": 0.6318537872284651, "entropy": 0.6360546965152025, "sharp": 0.14198052696883678}
|
| 54 |
+
{"time": "12:23:56", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 874.2588882022271, "loss": 0.6480370759963989, "entropy": 0.6473933756351471, "sharp": 0.11683804169297218}
|
| 55 |
+
{"time": "12:27:35", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 874.6643402276964, "loss": 0.6334035154432058, "entropy": 0.6499393992125988, "sharp": 0.12684703432023525}
|
| 56 |
+
{"time": "12:28:58", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5850250124931335, "noul_T": 0.7595249686054862, "noul_auc": 0.7318188722553206, "noul_acc": 0.702, "noul_f1": 0.7682737169517885, "noul_nll": 0.590603579364717, "noul_ece": 0.06252238416671752, "noul_brier": 0.20186487573155232, "noul_sharp": 0.1538901925086975, "entropy": 0.6182107925415039}
|
| 57 |
+
{"time": "12:31:59", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9820167, "tok_per_s": 854.7992102709214, "rows_per_s": 1.4660166465301607, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5699275732040405, "noul_T": 0.7724464809625557, "choice_ce": 0.6716148257255554, "choice_T": 1.0270244461420386, "score_ce": 1.0511720180511475, "score_T": 0.9929109453941127, "noul_auc": 0.7252821333333332, "noul_acc": 0.699, "noul_f1": 0.7762081784386617, "noul_nll": 0.5881762043386698, "noul_ece": 0.059616081506013885, "noul_brier": 0.201311856030733, "noul_sharp": 0.1597384661436081, "entropy": 0.6134923100471497}, "dropped_long": 0, "peak_gib": 18.236003875732422}
|
e33/S1-E33-M10-rt-n16k-syn/DONE
ADDED
|
@@ -0,0 +1 @@
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| 1 |
+
2026-10-23 04:32:35
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/README.md
ADDED
|
@@ -0,0 +1,206 @@
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|
| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
|
|
|
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|
| 1 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 7 |
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|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
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"bias": "none",
|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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"exclude_modules": null,
|
| 15 |
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|
| 16 |
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"inference_mode": true,
|
| 17 |
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"init_lora_weights": true,
|
| 18 |
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"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"v_proj",
|
| 40 |
+
"k_proj",
|
| 41 |
+
"q_proj",
|
| 42 |
+
"up_proj",
|
| 43 |
+
"in_proj_qkv",
|
| 44 |
+
"gate_proj",
|
| 45 |
+
"in_proj_z",
|
| 46 |
+
"down_proj",
|
| 47 |
+
"o_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
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"task_type": null,
|
| 51 |
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"trainable_token_indices": null,
|
| 52 |
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"use_bdlora": null,
|
| 53 |
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"use_dora": false,
|
| 54 |
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"use_qalora": false,
|
| 55 |
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"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
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|
|
|
|
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|
| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:acd7398bcc7b780b9076cd2cd710473219c65da73c87a462f1bf7db725e9bcd1
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| 3 |
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size 160486456
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
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|
| 7 |
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|
| 8 |
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"k_proj",
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"lm_head",
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|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/adapter_vllm/decision_head.json
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"L",
|
| 91 |
+
"M",
|
| 92 |
+
"N",
|
| 93 |
+
"O",
|
| 94 |
+
"P"
|
| 95 |
+
],
|
| 96 |
+
"template_version": "bare-v1"
|
| 97 |
+
},
|
| 98 |
+
"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
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|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
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|
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|
|
|
|
|
|
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|
|
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|
|
| 1 |
+
{
|
| 2 |
+
"version": 1,
|
| 3 |
+
"per_kind": {
|
| 4 |
+
"noul": 0.7800532877395329,
|
| 5 |
+
"choice": 1.0466806238139477,
|
| 6 |
+
"score": 0.9804041633946682
|
| 7 |
+
},
|
| 8 |
+
"fit": {
|
| 9 |
+
"noul": {
|
| 10 |
+
"n": 1087,
|
| 11 |
+
"T": 0.7800532877395329,
|
| 12 |
+
"ce_before": 0.5706181526184082,
|
| 13 |
+
"ce_after": 0.5660994648933411
|
| 14 |
+
},
|
| 15 |
+
"choice": {
|
| 16 |
+
"n": 60,
|
| 17 |
+
"T": 1.0466806238139477,
|
| 18 |
+
"ce_before": 0.672325849533081,
|
| 19 |
+
"ce_after": 0.6718399524688721
|
| 20 |
+
},
|
| 21 |
+
"score": {
|
| 22 |
+
"n": 53,
|
| 23 |
+
"T": 0.9804041633946682,
|
| 24 |
+
"ce_before": 1.0526014566421509,
|
| 25 |
+
"ce_after": 1.0524842739105225
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"source": "models/e33/S1-E33-M10-rt-n16k-syn/ckpt-16000"
|
| 29 |
+
}
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a1ea418ef3e6efca8f1a8bd124c42306c9abf5f03aae0d9dec4a89cf24f60687
|
| 3 |
+
size 393464
|
e33/S1-E33-M10-rt-n16k-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
|
|
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|
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|
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|
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|
|
|
|
|
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|
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|
|
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|
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"base_model_path": "/root/models/Qwen3.5-9B",
|
| 3 |
+
"hidden_size": 4096,
|
| 4 |
+
"slots": {
|
| 5 |
+
"num_slots": 24,
|
| 6 |
+
"ranges": {
|
| 7 |
+
"noul": [
|
| 8 |
+
0,
|
| 9 |
+
2
|
| 10 |
+
],
|
| 11 |
+
"score": [
|
| 12 |
+
2,
|
| 13 |
+
8
|
| 14 |
+
],
|
| 15 |
+
"choice": [
|
| 16 |
+
8,
|
| 17 |
+
24
|
| 18 |
+
]
|
| 19 |
+
},
|
| 20 |
+
"verbalizers": [
|
| 21 |
+
"false",
|
| 22 |
+
"true",
|
| 23 |
+
"0",
|
| 24 |
+
"1",
|
| 25 |
+
"2",
|
| 26 |
+
"3",
|
| 27 |
+
"4",
|
| 28 |
+
"5",
|
| 29 |
+
"A",
|
| 30 |
+
"B",
|
| 31 |
+
"C",
|
| 32 |
+
"D",
|
| 33 |
+
"E",
|
| 34 |
+
"F",
|
| 35 |
+
"G",
|
| 36 |
+
"H",
|
| 37 |
+
"I",
|
| 38 |
+
"J",
|
| 39 |
+
"K",
|
| 40 |
+
"L",
|
| 41 |
+
"M",
|
| 42 |
+
"N",
|
| 43 |
+
"O",
|
| 44 |
+
"P"
|
| 45 |
+
],
|
| 46 |
+
"template_version": "bare-v1"
|
| 47 |
+
},
|
| 48 |
+
"verbalizer_ids": [
|
| 49 |
+
3721,
|
| 50 |
+
1802,
|
| 51 |
+
15,
|
| 52 |
+
16,
|
| 53 |
+
17,
|
| 54 |
+
18,
|
| 55 |
+
19,
|
| 56 |
+
20,
|
| 57 |
+
32,
|
| 58 |
+
33,
|
| 59 |
+
34,
|
| 60 |
+
35,
|
| 61 |
+
36,
|
| 62 |
+
37,
|
| 63 |
+
38,
|
| 64 |
+
39,
|
| 65 |
+
40,
|
| 66 |
+
41,
|
| 67 |
+
42,
|
| 68 |
+
43,
|
| 69 |
+
44,
|
| 70 |
+
45,
|
| 71 |
+
46,
|
| 72 |
+
47
|
| 73 |
+
],
|
| 74 |
+
"kinds": [
|
| 75 |
+
"noul",
|
| 76 |
+
"choice",
|
| 77 |
+
"score"
|
| 78 |
+
],
|
| 79 |
+
"model_name": "jev-judge-qwen35-9b",
|
| 80 |
+
"model_version": "0.8.0",
|
| 81 |
+
"lm_head_included": true,
|
| 82 |
+
"weights_mode": "unmerged",
|
| 83 |
+
"adapter_subfolder": "adapter",
|
| 84 |
+
"lora": {
|
| 85 |
+
"r": 16,
|
| 86 |
+
"lora_alpha": 32,
|
| 87 |
+
"lora_dropout": 0.05,
|
| 88 |
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"target_modules": [
|
| 89 |
+
"down_proj",
|
| 90 |
+
"gate_proj",
|
| 91 |
+
"in_proj_qkv",
|
| 92 |
+
"in_proj_z",
|
| 93 |
+
"k_proj",
|
| 94 |
+
"o_proj",
|
| 95 |
+
"out_proj",
|
| 96 |
+
"q_proj",
|
| 97 |
+
"up_proj",
|
| 98 |
+
"v_proj"
|
| 99 |
+
]
|
| 100 |
+
},
|
| 101 |
+
"trained_stage": "e16",
|
| 102 |
+
"source_checkpoint": "models/e33/S1-E33-M10-rt-n16k-syn/ckpt-16000",
|
| 103 |
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"softcap": null,
|
| 104 |
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"e16": {
|
| 105 |
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"data": "data/e33/E33-M10-rt-n16k",
|
| 106 |
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"data_manifest": {
|
| 107 |
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"arm": "E33-M10-rt-n16k",
|
| 108 |
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"name": null,
|
| 109 |
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"train_sha256": "39574ddaa158a99572227f29fcc2be761352b45f2f70805ff1c7883379ef2228",
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| 110 |
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"n_train": 16000
|
| 111 |
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},
|
| 112 |
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"init": "released",
|
| 113 |
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"objective": "s-log",
|
| 114 |
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"sigma": 0.5,
|
| 115 |
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"K": 8,
|
| 116 |
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"reward": "brier",
|
| 117 |
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"clip": 0.2,
|
| 118 |
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"passes": 1,
|
| 119 |
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"lr": 0.0001,
|
| 120 |
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"lr_head": 0.0002,
|
| 121 |
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"rows_per_step": 32,
|
| 122 |
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"train_seed": 0,
|
| 123 |
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"replay": "data/e16/replay/train.jsonl",
|
| 124 |
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"replay_frac": 0.05,
|
| 125 |
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"replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e",
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| 126 |
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"max_len": 3072,
|
| 127 |
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"schedule": "warmup 0.03 + cosine to x0.05 over 500 steps",
|
| 128 |
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"total_rows": 16000,
|
| 129 |
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"lora": {
|
| 130 |
+
"r": 16,
|
| 131 |
+
"lora_alpha": 32,
|
| 132 |
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"lora_dropout": 0.05
|
| 133 |
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},
|
| 134 |
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"trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3",
|
| 135 |
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"event": "ckpt",
|
| 136 |
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"tag": "ckpt-16000",
|
| 137 |
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"rows_seen": 16000,
|
| 138 |
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"replay_seen": 842,
|
| 139 |
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"step": 500,
|
| 140 |
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"tokens": 9820167,
|
| 141 |
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"tok_per_s": 853.3575821037343,
|
| 142 |
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"rows_per_s": 1.4635441932658964,
|
| 143 |
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"val": {
|
| 144 |
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"n": 1200,
|
| 145 |
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"dropped_long": 0,
|
| 146 |
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"noul_ce": 0.5706181526184082,
|
| 147 |
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"noul_T": 0.7800532877395329,
|
| 148 |
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"choice_ce": 0.672325849533081,
|
| 149 |
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"choice_T": 1.0466806238139477,
|
| 150 |
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"score_ce": 1.0526014566421509,
|
| 151 |
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"score_T": 0.9804041633946682,
|
| 152 |
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"noul_auc": 0.7283541333333334,
|
| 153 |
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"noul_acc": 0.698,
|
| 154 |
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"noul_f1": 0.7719033232628398,
|
| 155 |
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"noul_nll": 0.5866083004325628,
|
| 156 |
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"noul_ece": 0.05212497982382775,
|
| 157 |
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"noul_brier": 0.20057906316333285,
|
| 158 |
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"noul_sharp": 0.16233906149864197,
|
| 159 |
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"entropy": 0.6147943139076233
|
| 160 |
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},
|
| 161 |
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"dropped_long": 0,
|
| 162 |
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"peak_gib": 18.236003875732422
|
| 163 |
+
}
|
| 164 |
+
}
|
e33/S1-E33-M10-rt-n16k-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"time": "01:20:46", "event": "start", "data": "data/e33/E33-M10-rt-n16k", "data_manifest": {"arm": "E33-M10-rt-n16k", "name": null, "train_sha256": "39574ddaa158a99572227f29fcc2be761352b45f2f70805ff1c7883379ef2228", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 68.17974424362183}
|
| 2 |
+
{"time": "01:24:26", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 894.3302368416892, "loss": 0.6407141238451004, "entropy": 0.6530866995453835, "sharp": 0.11467453930526972}
|
| 3 |
+
{"time": "01:28:07", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 898.5712368978669, "loss": 0.7670875117182732, "entropy": 0.5850043445825577, "sharp": 0.19216507486999035}
|
| 4 |
+
{"time": "01:31:47", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 901.0519607560497, "loss": 0.7097546458244324, "entropy": 0.5784373320639133, "sharp": 0.2102995691820979}
|
| 5 |
+
{"time": "01:35:19", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 900.2845654414082, "loss": 0.7051415480673313, "entropy": 0.6509120985865593, "sharp": 0.11466245353221893}
|
| 6 |
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{"time": "01:38:52", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 899.3461954764921, "loss": 0.6417021974921227, "entropy": 0.6230399906635284, "sharp": 0.16287371329963207}
|
| 7 |
+
{"time": "01:42:32", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 902.1724212711766, "loss": 0.5933823697268963, "entropy": 0.6530337370932102, "sharp": 0.1106806006282568}
|
| 8 |
+
{"time": "01:46:04", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 902.7435101228933, "loss": 0.6372644007205963, "entropy": 0.6816029846668243, "sharp": 0.060833889059722424}
|
| 9 |
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{"time": "01:49:43", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 901.7272742006631, "loss": 0.6699827425181866, "entropy": 0.6287437509745359, "sharp": 0.1442428957670927}
|
| 10 |
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{"time": "01:53:15", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 901.3173038745224, "loss": 0.6240650974214077, "entropy": 0.6412920206785202, "sharp": 0.1320671895518899}
|
| 11 |
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{"time": "01:57:00", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 901.9174655351277, "loss": 0.6517882402986288, "entropy": 0.6239370983093977, "sharp": 0.15501127019524574}
|
| 12 |
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{"time": "01:58:23", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.5938156843185425, "noul_T": 0.7507550395879644, "noul_auc": 0.7372365023375133, "noul_acc": 0.714, "noul_f1": 0.7906295754026355, "noul_nll": 0.5917655223309993, "noul_ece": 0.06725453257560729, "noul_brier": 0.20199009536325635, "noul_sharp": 0.14850011467933655, "entropy": 0.6278250813484192}
|
| 13 |
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{"time": "02:02:00", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 871.1336387513961, "loss": 0.6488936170935631, "entropy": 0.6459421142935753, "sharp": 0.1318453261628747}
|
| 14 |
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{"time": "02:05:30", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 873.0455970204106, "loss": 0.6333391219377518, "entropy": 0.6602405309677124, "sharp": 0.0976364342495799}
|
| 15 |
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{"time": "02:09:03", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 874.8895332796241, "loss": 0.646759383380413, "entropy": 0.5998613610863686, "sharp": 0.1769361738115549}
|
| 16 |
+
{"time": "02:12:40", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 876.7330429188311, "loss": 0.6052324529737234, "entropy": 0.6510478630661964, "sharp": 0.10768228489905596}
|
| 17 |
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{"time": "02:16:15", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 878.2464503690718, "loss": 0.6153158433735371, "entropy": 0.631971400231123, "sharp": 0.16027738526463509}
|
| 18 |
+
{"time": "02:19:55", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 879.2137809500738, "loss": 0.6790948957204819, "entropy": 0.5736175198107958, "sharp": 0.20291051920503378}
|
| 19 |
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{"time": "02:23:29", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 880.3711935175188, "loss": 0.6004719063639641, "entropy": 0.6468684375286102, "sharp": 0.12351896334439516}
|
| 20 |
+
{"time": "02:27:06", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 881.5599301165362, "loss": 0.6054106764495373, "entropy": 0.6608152016997337, "sharp": 0.09726034570485353}
|
| 21 |
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{"time": "02:30:42", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 882.3999166719803, "loss": 0.6535965269431472, "entropy": 0.6553077027201653, "sharp": 0.11877382826060057}
|
| 22 |
+
{"time": "02:34:22", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 883.6472831287725, "loss": 0.61347995698452, "entropy": 0.6301144063472748, "sharp": 0.14622782915830612}
|
| 23 |
+
{"time": "02:35:45", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.5859304070472717, "noul_T": 0.8799948384607998, "noul_auc": 0.7436330188520024, "noul_acc": 0.716, "noul_f1": 0.7874251497005988, "noul_nll": 0.5828873897492886, "noul_ece": 0.06448433697223664, "noul_brier": 0.1981293654491963, "noul_sharp": 0.17154835164546967, "entropy": 0.6047180891036987}
|
| 24 |
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{"time": "02:39:28", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 869.194350995947, "loss": 0.6664544409140944, "entropy": 0.6718409713357687, "sharp": 0.08500322513282299}
|
| 25 |
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{"time": "02:43:03", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 870.3098890608844, "loss": 0.6444327458739281, "entropy": 0.6366416960954666, "sharp": 0.13889538496732712}
|
| 26 |
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{"time": "02:46:45", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 870.9679598953579, "loss": 0.6266806535422802, "entropy": 0.6547847539186478, "sharp": 0.11867003049701452}
|
| 27 |
+
{"time": "02:50:25", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 872.162954408354, "loss": 0.6558815725147724, "entropy": 0.6340029835700989, "sharp": 0.1507103629410267}
|
| 28 |
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{"time": "02:54:06", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 873.4662758411903, "loss": 0.642772326245904, "entropy": 0.6260318588465452, "sharp": 0.16632072255015373}
|
| 29 |
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{"time": "02:57:47", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 874.4971117879062, "loss": 0.6335619688034058, "entropy": 0.6518338844180107, "sharp": 0.12628033384680748}
|
| 30 |
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{"time": "03:01:20", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 875.2975710934581, "loss": 0.6495114751160145, "entropy": 0.6683188453316689, "sharp": 0.09399524331092834}
|
| 31 |
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{"time": "03:04:59", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 875.8806219727835, "loss": 0.6487135104835033, "entropy": 0.6416224911808968, "sharp": 0.1189706027507782}
|
| 32 |
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{"time": "03:08:29", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 876.5671341788939, "loss": 0.6583934891968966, "entropy": 0.6552927903831005, "sharp": 0.11414727661758661}
|
| 33 |
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{"time": "03:12:12", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 877.6184190910565, "loss": 0.661140576004982, "entropy": 0.6403373926877975, "sharp": 0.13451462611556053}
|
| 34 |
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{"time": "03:13:36", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5856049656867981, "noul_T": 0.8816176327090242, "noul_auc": 0.7410507839530135, "noul_acc": 0.684, "noul_f1": 0.7799442896935933, "noul_nll": 0.5889199020117521, "noul_ece": 0.07037900412082672, "noul_brier": 0.20162840001933632, "noul_sharp": 0.1706424504518509, "entropy": 0.6040006875991821}
|
| 35 |
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{"time": "03:17:11", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 867.636449941811, "loss": 0.6064267233014107, "entropy": 0.6226922497153282, "sharp": 0.1504072267562151}
|
| 36 |
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{"time": "03:20:48", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 868.825550660966, "loss": 0.6666115932166576, "entropy": 0.6551536694169044, "sharp": 0.10939735546708107}
|
| 37 |
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{"time": "03:24:27", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 869.444203220318, "loss": 0.6336435861885548, "entropy": 0.6463650986552238, "sharp": 0.12483089882880449}
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| 38 |
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{"time": "03:28:03", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 870.5032601087813, "loss": 0.6576888412237167, "entropy": 0.6181784169748425, "sharp": 0.1659212587401271}
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| 39 |
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{"time": "03:31:44", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 871.4820855569737, "loss": 0.6604277305305004, "entropy": 0.6469684541225433, "sharp": 0.11548988427966833}
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| 40 |
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{"time": "03:35:20", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 872.2455562457085, "loss": 0.6381114348769188, "entropy": 0.6450099423527718, "sharp": 0.11503359023481607}
|
| 41 |
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{"time": "03:39:04", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 872.8070292594366, "loss": 0.6908784322440624, "entropy": 0.633655920624733, "sharp": 0.13484611455351114}
|
| 42 |
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{"time": "03:42:33", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 873.3877540759133, "loss": 0.6250544004142284, "entropy": 0.6358201876282692, "sharp": 0.1346720615401864}
|
| 43 |
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{"time": "03:46:14", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 873.9114803828065, "loss": 0.6878696195781231, "entropy": 0.6477202232927084, "sharp": 0.10971695929765701}
|
| 44 |
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{"time": "03:50:00", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 874.7192303517428, "loss": 0.6515332609415054, "entropy": 0.6342602297663689, "sharp": 0.13561679888516665}
|
| 45 |
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{"time": "03:51:23", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5833331346511841, "noul_T": 0.8217515025225614, "noul_auc": 0.740055020168436, "noul_acc": 0.714, "noul_f1": 0.7816793893129771, "noul_nll": 0.584851800262928, "noul_ece": 0.05926298546791077, "noul_brier": 0.1992804793556761, "noul_sharp": 0.16393373906612396, "entropy": 0.6101114749908447}
|
| 46 |
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{"time": "03:55:05", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 867.5312933374554, "loss": 0.627738818526268, "entropy": 0.6642075832933187, "sharp": 0.09371273778378963}
|
| 47 |
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{"time": "03:58:49", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 868.4505163717379, "loss": 0.5989300683140755, "entropy": 0.6216349601745605, "sharp": 0.15461522340774536}
|
| 48 |
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{"time": "04:02:35", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 869.1675793578265, "loss": 0.6381424367427826, "entropy": 0.6140604615211487, "sharp": 0.15680895280092955}
|
| 49 |
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{"time": "04:06:12", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 869.8846409524637, "loss": 0.6422123610973358, "entropy": 0.6449132598936558, "sharp": 0.12053444609045982}
|
| 50 |
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{"time": "04:09:58", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 870.5906451027971, "loss": 0.6214579604566097, "entropy": 0.6666248366236687, "sharp": 0.09311869088560343}
|
| 51 |
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{"time": "04:13:35", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 871.2019719938318, "loss": 0.6460805404931307, "entropy": 0.6567777544260025, "sharp": 0.1107736174017191}
|
| 52 |
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{"time": "04:17:13", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 871.8909668828694, "loss": 0.6471943072974682, "entropy": 0.6520841270685196, "sharp": 0.12355391774326563}
|
| 53 |
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{"time": "04:20:53", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 872.1641297327224, "loss": 0.6499506458640099, "entropy": 0.6403382867574692, "sharp": 0.13805944379419088}
|
| 54 |
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{"time": "04:24:34", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 872.7285434720358, "loss": 0.6431107819080353, "entropy": 0.6519273668527603, "sharp": 0.11090059950947762}
|
| 55 |
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{"time": "04:28:13", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 873.1511200997285, "loss": 0.6419705078005791, "entropy": 0.6479619462043047, "sharp": 0.12581786420196295}
|
| 56 |
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{"time": "04:29:36", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5854170918464661, "noul_T": 0.7670265124397351, "noul_auc": 0.7415402271691616, "noul_acc": 0.712, "noul_f1": 0.7714285714285715, "noul_nll": 0.5860456532686948, "noul_ece": 0.062291146516799935, "noul_brier": 0.19968873407987509, "noul_sharp": 0.15745879709720612, "entropy": 0.6191316246986389}
|
| 57 |
+
{"time": "04:32:35", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9820167, "tok_per_s": 853.3575821037343, "rows_per_s": 1.4635441932658964, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5706181526184082, "noul_T": 0.7800532877395329, "choice_ce": 0.672325849533081, "choice_T": 1.0466806238139477, "score_ce": 1.0526014566421509, "score_T": 0.9804041633946682, "noul_auc": 0.7283541333333334, "noul_acc": 0.698, "noul_f1": 0.7719033232628398, "noul_nll": 0.5866083004325628, "noul_ece": 0.05212497982382775, "noul_brier": 0.20057906316333285, "noul_sharp": 0.16233906149864197, "entropy": 0.6147943139076233}, "dropped_long": 0, "peak_gib": 18.236003875732422}
|
e33/S1-E33-M20P40-n16k-a100-syn/DONE
ADDED
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2026-10-23 17:35:55
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e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/README.md
ADDED
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| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"in_proj_z",
|
| 40 |
+
"down_proj",
|
| 41 |
+
"q_proj",
|
| 42 |
+
"v_proj",
|
| 43 |
+
"gate_proj",
|
| 44 |
+
"in_proj_qkv",
|
| 45 |
+
"up_proj",
|
| 46 |
+
"k_proj",
|
| 47 |
+
"o_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
+
"task_type": null,
|
| 51 |
+
"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
+
"use_dora": false,
|
| 54 |
+
"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4b06f968a6db3848efc7e61de7ca5803a555d400c261bfb55f4e605bd2cc15e8
|
| 3 |
+
size 160486456
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
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|
|
|
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|
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|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": null,
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 64.0,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.0,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 32,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"down_proj",
|
| 39 |
+
"gate_proj",
|
| 40 |
+
"in_proj_qkv",
|
| 41 |
+
"in_proj_z",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"lm_head",
|
| 44 |
+
"o_proj",
|
| 45 |
+
"out_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
+
"up_proj",
|
| 48 |
+
"v_proj"
|
| 49 |
+
],
|
| 50 |
+
"target_parameters": null,
|
| 51 |
+
"task_type": null,
|
| 52 |
+
"trainable_token_indices": null,
|
| 53 |
+
"use_bdlora": null,
|
| 54 |
+
"use_dora": false,
|
| 55 |
+
"use_qalora": false,
|
| 56 |
+
"use_rslora": false,
|
| 57 |
+
"velora_config": null
|
| 58 |
+
}
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:343b9dba12d72646e7c3cad503764c38b9b9bda2d18b929dffd0341d2715f4dc
|
| 3 |
+
size 176641832
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bias": [
|
| 3 |
+
0.00010125698463525623,
|
| 4 |
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|
| 5 |
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0.0011667461367323995,
|
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|
| 11 |
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|
| 12 |
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|
| 13 |
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0.0002803638344630599,
|
| 14 |
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0.0005846124258823693,
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| 15 |
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| 19 |
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| 20 |
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| 22 |
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| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
+
3721,
|
| 30 |
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1802,
|
| 31 |
+
15,
|
| 32 |
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16,
|
| 33 |
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17,
|
| 34 |
+
18,
|
| 35 |
+
19,
|
| 36 |
+
20,
|
| 37 |
+
32,
|
| 38 |
+
33,
|
| 39 |
+
34,
|
| 40 |
+
35,
|
| 41 |
+
36,
|
| 42 |
+
37,
|
| 43 |
+
38,
|
| 44 |
+
39,
|
| 45 |
+
40,
|
| 46 |
+
41,
|
| 47 |
+
42,
|
| 48 |
+
43,
|
| 49 |
+
44,
|
| 50 |
+
45,
|
| 51 |
+
46,
|
| 52 |
+
47
|
| 53 |
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],
|
| 54 |
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"slots": {
|
| 55 |
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"num_slots": 24,
|
| 56 |
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"ranges": {
|
| 57 |
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"noul": [
|
| 58 |
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0,
|
| 59 |
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|
| 60 |
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],
|
| 61 |
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"score": [
|
| 62 |
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|
| 63 |
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|
| 64 |
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],
|
| 65 |
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"choice": [
|
| 66 |
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8,
|
| 67 |
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24
|
| 68 |
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]
|
| 69 |
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},
|
| 70 |
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"verbalizers": [
|
| 71 |
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"false",
|
| 72 |
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"true",
|
| 73 |
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"0",
|
| 74 |
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"1",
|
| 75 |
+
"2",
|
| 76 |
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"3",
|
| 77 |
+
"4",
|
| 78 |
+
"5",
|
| 79 |
+
"A",
|
| 80 |
+
"B",
|
| 81 |
+
"C",
|
| 82 |
+
"D",
|
| 83 |
+
"E",
|
| 84 |
+
"F",
|
| 85 |
+
"G",
|
| 86 |
+
"H",
|
| 87 |
+
"I",
|
| 88 |
+
"J",
|
| 89 |
+
"K",
|
| 90 |
+
"L",
|
| 91 |
+
"M",
|
| 92 |
+
"N",
|
| 93 |
+
"O",
|
| 94 |
+
"P"
|
| 95 |
+
],
|
| 96 |
+
"template_version": "bare-v1"
|
| 97 |
+
},
|
| 98 |
+
"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"version": 1,
|
| 3 |
+
"per_kind": {
|
| 4 |
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"noul": 0.8002108628973789,
|
| 5 |
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"choice": 1.0728412258162334,
|
| 6 |
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"score": 0.9491235278105069
|
| 7 |
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},
|
| 8 |
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"fit": {
|
| 9 |
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"noul": {
|
| 10 |
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"n": 1087,
|
| 11 |
+
"T": 0.8002108628973789,
|
| 12 |
+
"ce_before": 0.5691902041435242,
|
| 13 |
+
"ce_after": 0.5654259920120239
|
| 14 |
+
},
|
| 15 |
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"choice": {
|
| 16 |
+
"n": 60,
|
| 17 |
+
"T": 1.0728412258162334,
|
| 18 |
+
"ce_before": 0.6705418825149536,
|
| 19 |
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"ce_after": 0.6693586111068726
|
| 20 |
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|
| 21 |
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"score": {
|
| 22 |
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"n": 53,
|
| 23 |
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"T": 0.9491235278105069,
|
| 24 |
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|
| 25 |
+
"ce_after": 1.0447719097137451
|
| 26 |
+
}
|
| 27 |
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},
|
| 28 |
+
"source": "models/e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000"
|
| 29 |
+
}
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
|
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|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:9e7dd06ef2275896db2a9ad8e41f09f0ef7babb8b31997efa4d1e3e013489b25
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| 3 |
+
size 393464
|
e33/S1-E33-M20P40-n16k-a100-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"base_model_path": "/root/models/Qwen3.5-9B",
|
| 3 |
+
"hidden_size": 4096,
|
| 4 |
+
"slots": {
|
| 5 |
+
"num_slots": 24,
|
| 6 |
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|
| 7 |
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"noul": [
|
| 8 |
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0,
|
| 9 |
+
2
|
| 10 |
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],
|
| 11 |
+
"score": [
|
| 12 |
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2,
|
| 13 |
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8
|
| 14 |
+
],
|
| 15 |
+
"choice": [
|
| 16 |
+
8,
|
| 17 |
+
24
|
| 18 |
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]
|
| 19 |
+
},
|
| 20 |
+
"verbalizers": [
|
| 21 |
+
"false",
|
| 22 |
+
"true",
|
| 23 |
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"0",
|
| 24 |
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"1",
|
| 25 |
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"2",
|
| 26 |
+
"3",
|
| 27 |
+
"4",
|
| 28 |
+
"5",
|
| 29 |
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"A",
|
| 30 |
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"B",
|
| 31 |
+
"C",
|
| 32 |
+
"D",
|
| 33 |
+
"E",
|
| 34 |
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"F",
|
| 35 |
+
"G",
|
| 36 |
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"H",
|
| 37 |
+
"I",
|
| 38 |
+
"J",
|
| 39 |
+
"K",
|
| 40 |
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"L",
|
| 41 |
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"M",
|
| 42 |
+
"N",
|
| 43 |
+
"O",
|
| 44 |
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"P"
|
| 45 |
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],
|
| 46 |
+
"template_version": "bare-v1"
|
| 47 |
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},
|
| 48 |
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"verbalizer_ids": [
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| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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18,
|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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36,
|
| 62 |
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|
| 63 |
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38,
|
| 64 |
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39,
|
| 65 |
+
40,
|
| 66 |
+
41,
|
| 67 |
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42,
|
| 68 |
+
43,
|
| 69 |
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44,
|
| 70 |
+
45,
|
| 71 |
+
46,
|
| 72 |
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47
|
| 73 |
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],
|
| 74 |
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"kinds": [
|
| 75 |
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"noul",
|
| 76 |
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"choice",
|
| 77 |
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"score"
|
| 78 |
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],
|
| 79 |
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"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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"model_version": "0.8.0",
|
| 81 |
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"lm_head_included": true,
|
| 82 |
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"weights_mode": "unmerged",
|
| 83 |
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"adapter_subfolder": "adapter",
|
| 84 |
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"lora": {
|
| 85 |
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"r": 16,
|
| 86 |
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|
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|
| 88 |
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|
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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},
|
| 101 |
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|
| 102 |
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| 103 |
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"e16": {
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| 105 |
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"data": "data/e33/E33-M20P40-n16k-a100",
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|
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|
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|
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|
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|
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|
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|
| 164 |
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}
|
e33/S1-E33-M20P40-n16k-a100-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
|
|
|
|
|
|
|
|
|
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| 1 |
+
{"time": "14:13:08", "event": "start", "data": "data/e33/E33-M20P40-n16k-a100", "data_manifest": {"arm": "E33-M20P40-n16k-a100", "name": null, "train_sha256": "4c2cbc7e61a30f31b9bd5413d5605555b3ac9485e7e3cb9e113abd1aa1394b12", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 120.29126191139221}
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| 2 |
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{"time": "14:16:54", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 839.8715478391055, "loss": 0.6187404282391071, "entropy": 0.6414551772177219, "sharp": 0.13162385113537312}
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| 3 |
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{"time": "14:20:44", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 847.5550024837847, "loss": 0.710713678970933, "entropy": 0.6639010868966579, "sharp": 0.094074378721416}
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| 4 |
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{"time": "14:24:42", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 846.8465414505208, "loss": 0.7149962484836578, "entropy": 0.6894855201244354, "sharp": 0.038734118454158306}
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| 5 |
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{"time": "14:28:40", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 847.0194710535048, "loss": 0.7016126066446304, "entropy": 0.6360101252794266, "sharp": 0.15717380121350288}
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| 6 |
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{"time": "14:32:21", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 846.5476430796652, "loss": 0.7025396898388863, "entropy": 0.6633415594696999, "sharp": 0.09588960744440556}
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| 7 |
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{"time": "14:36:18", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 847.856212094996, "loss": 0.6576686762273312, "entropy": 0.5767230838537216, "sharp": 0.2077706828713417}
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| 8 |
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{"time": "14:40:04", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 849.3255868206792, "loss": 0.7632252350449562, "entropy": 0.6031612306833267, "sharp": 0.1766234626993537}
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| 9 |
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{"time": "14:43:56", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 848.8644693577511, "loss": 0.562406275421381, "entropy": 0.5192938018590212, "sharp": 0.2664580028504133}
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| 10 |
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{"time": "14:47:44", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 847.7852483871987, "loss": 0.677379759028554, "entropy": 0.6627754978835583, "sharp": 0.10070306714624166}
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| 11 |
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| 12 |
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{"time": "14:53:08", "event": "val", "step": 100, "rows_seen": 3200, "n": 500, "dropped_long": 0, "noul_ce": 0.6212870478630066, "noul_T": 0.7023261478585969, "noul_auc": 0.6843260029366593, "noul_acc": 0.672, "noul_f1": 0.7759562841530054, "noul_nll": 0.6250243791341782, "noul_ece": 0.11322395074367522, "noul_brier": 0.21671475337394724, "noul_sharp": 0.12332789599895477, "entropy": 0.6514794230461121}
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| 13 |
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{"time": "14:56:48", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 818.6033910951888, "loss": 0.6246248260140419, "entropy": 0.604729138314724, "sharp": 0.19723656587302685}
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| 14 |
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{"time": "15:00:34", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 820.7401742662969, "loss": 0.7470029867254198, "entropy": 0.5473670903593302, "sharp": 0.24039341136813164}
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| 15 |
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{"time": "15:04:22", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 822.128574168893, "loss": 0.6280730292201042, "entropy": 0.6206810176372528, "sharp": 0.16349924262613058}
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| 16 |
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{"time": "15:08:05", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 823.5858737424818, "loss": 0.6877431944012642, "entropy": 0.6785900443792343, "sharp": 0.07349966000765562}
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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{"time": "15:32:43", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.6128379106521606, "noul_T": 0.47963188571230614, "noul_auc": 0.7305193161296856, "noul_acc": 0.7, "noul_f1": 0.7572815533980582, "noul_nll": 0.6143106191158295, "noul_ece": 0.1173224647641182, "noul_brier": 0.21178017520018558, "noul_sharp": 0.10002126544713974, "entropy": 0.6633838415145874}
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| 24 |
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{"time": "15:36:35", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 818.3244384803786, "loss": 0.6299922671169043, "entropy": 0.6626281999051571, "sharp": 0.10336934588849545}
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| 25 |
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{"time": "15:40:22", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 819.8278409393922, "loss": 0.627080044709146, "entropy": 0.6587131060659885, "sharp": 0.11120752524584532}
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| 26 |
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{"time": "15:44:19", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 820.8217398785365, "loss": 0.5289444080553949, "entropy": 0.6182603435590863, "sharp": 0.16458167880773544}
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| 27 |
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{"time": "15:48:16", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 821.7753717182602, "loss": 0.668922908604145, "entropy": 0.5956772342324257, "sharp": 0.19893265888094902}
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| 28 |
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{"time": "15:52:13", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 822.6517675023122, "loss": 0.6773939281702042, "entropy": 0.6701566651463509, "sharp": 0.08436406124383211}
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| 29 |
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{"time": "15:55:57", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 823.7591338250224, "loss": 0.6251176791265607, "entropy": 0.6630509197711945, "sharp": 0.10360329411923885}
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| 30 |
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{"time": "15:59:46", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 825.0068217712911, "loss": 0.698808241635561, "entropy": 0.5815245062112808, "sharp": 0.21828553080558777}
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| 31 |
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{"time": "16:03:35", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 826.2237881602903, "loss": 0.7049896717071533, "entropy": 0.654325544834137, "sharp": 0.09251557663083076}
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| 32 |
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{"time": "16:07:26", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 827.1292792775448, "loss": 0.688546247780323, "entropy": 0.6717874817550182, "sharp": 0.08574923686683178}
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| 33 |
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{"time": "16:11:15", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 827.914890733714, "loss": 0.49946608766913414, "entropy": 0.5843364968895912, "sharp": 0.20784184522926807}
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| 34 |
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{"time": "16:12:44", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.605241060256958, "noul_T": 1.2048853041749858, "noul_auc": 0.7253042142748646, "noul_acc": 0.636, "noul_f1": 0.7672634271099744, "noul_nll": 0.6115475974157453, "noul_ece": 0.13372548961639405, "noul_brier": 0.21162126575926385, "noul_sharp": 0.2091650366783142, "entropy": 0.5707269906997681}
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| 35 |
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{"time": "16:16:32", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 818.8158304626734, "loss": 0.5467460304498672, "entropy": 0.5993260815739632, "sharp": 0.18954907543957233}
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| 36 |
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{"time": "16:20:26", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 820.0792956300551, "loss": 0.6160920187830925, "entropy": 0.6452987492084503, "sharp": 0.13316628709435463}
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| 37 |
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{"time": "16:24:14", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 821.1997374291061, "loss": 0.5811580680310726, "entropy": 0.6088825017213821, "sharp": 0.16268229950219393}
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| 38 |
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{"time": "16:28:05", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 821.9665063572719, "loss": 0.6118759140372276, "entropy": 0.6484171822667122, "sharp": 0.12860039994120598}
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| 39 |
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{"time": "16:31:58", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 822.97676320785, "loss": 0.7243249639868736, "entropy": 0.6476022303104401, "sharp": 0.1273578805848956}
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| 40 |
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{"time": "16:35:44", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 823.7959610682416, "loss": 0.6667574434541166, "entropy": 0.6401418969035149, "sharp": 0.11859891004860401}
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| 41 |
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{"time": "16:39:31", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 824.6030474215052, "loss": 0.6770539954304695, "entropy": 0.6548423916101456, "sharp": 0.11251895409077406}
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| 42 |
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{"time": "16:43:23", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 825.3579685095436, "loss": 0.683322167955339, "entropy": 0.6304250992834568, "sharp": 0.15285257250070572}
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| 43 |
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{"time": "16:47:17", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 825.9141744084313, "loss": 0.5915361074730754, "entropy": 0.6303008385002613, "sharp": 0.1420151386409998}
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| 44 |
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{"time": "16:51:08", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 826.6632978600414, "loss": 0.5277743395417929, "entropy": 0.637439914047718, "sharp": 0.13507275190204382}
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| 45 |
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{"time": "16:52:37", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5858119130134583, "noul_T": 0.7325064249704112, "noul_auc": 0.7344348618588715, "noul_acc": 0.702, "noul_f1": 0.7732115677321156, "noul_nll": 0.5899210872650147, "noul_ece": 0.06367846584320071, "noul_brier": 0.20153352968871333, "noul_sharp": 0.14930002391338348, "entropy": 0.6234035491943359}
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| 46 |
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{"time": "16:56:25", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 819.9214470641089, "loss": 0.589809961616993, "entropy": 0.6252590082585812, "sharp": 0.14650190621614456}
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| 47 |
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{"time": "17:00:14", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 820.7593532438311, "loss": 0.5925923585891724, "entropy": 0.6398867517709732, "sharp": 0.11890413705259562}
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| 48 |
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{"time": "17:04:05", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 821.6220787132297, "loss": 0.6462609097361565, "entropy": 0.6125414073467255, "sharp": 0.16461621969938278}
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| 49 |
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{"time": "17:07:57", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 822.3114539874771, "loss": 0.6334951892495155, "entropy": 0.6172429770231247, "sharp": 0.15678761340677738}
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| 50 |
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{"time": "17:11:47", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 823.0525671531353, "loss": 0.7070290148258209, "entropy": 0.6357797607779503, "sharp": 0.1409710068255663}
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| 51 |
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{"time": "17:15:34", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 823.6646668729059, "loss": 0.6082311794161797, "entropy": 0.6516525633633137, "sharp": 0.1177465096116066}
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| 52 |
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{"time": "17:19:30", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 824.2039480742526, "loss": 0.633880028501153, "entropy": 0.6386780217289925, "sharp": 0.13634685520082712}
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| 53 |
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{"time": "17:23:27", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 824.8682535596918, "loss": 0.5927850492298603, "entropy": 0.6280360221862793, "sharp": 0.1544718537479639}
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| 54 |
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{"time": "17:27:15", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 825.4752101102926, "loss": 0.6072592251002789, "entropy": 0.6435235626995564, "sharp": 0.12449884880334139}
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| 55 |
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{"time": "17:31:12", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 825.8721817850699, "loss": 0.5903935097157955, "entropy": 0.6376286670565605, "sharp": 0.14049519877880812}
|
| 56 |
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{"time": "17:32:41", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5839874148368835, "noul_T": 0.7941656377356624, "noul_auc": 0.7346711447908051, "noul_acc": 0.706, "noul_f1": 0.7699530516431925, "noul_nll": 0.5867154191732407, "noul_ece": 0.0668563278913498, "noul_brier": 0.2000565286770292, "noul_sharp": 0.1619034707546234, "entropy": 0.6146537661552429}
|
| 57 |
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{"time": "17:35:55", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9814579, "tok_per_s": 806.9924313028692, "rows_per_s": 1.384814012135178, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5691902041435242, "noul_T": 0.8002108628973789, "choice_ce": 0.6705418825149536, "choice_T": 1.0728412258162334, "score_ce": 1.0455740690231323, "score_T": 0.9491235278105069, "noul_auc": 0.7222741333333333, "noul_acc": 0.698, "noul_f1": 0.7739520958083832, "noul_nll": 0.5880829917564988, "noul_ece": 0.04662516665458681, "noul_brier": 0.20118704083871727, "noul_sharp": 0.1676119565963745, "entropy": 0.6107596158981323}, "dropped_long": 0, "peak_gib": 18.236003875732422}
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e33/S1-E33-M20P40-n16k-syn/DONE
ADDED
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2026-10-23 11:35:25
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/README.md
ADDED
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|
| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
| 12 |
+
"ensure_weight_tying": false,
|
| 13 |
+
"eva_config": null,
|
| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
|
| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
|
| 18 |
+
"kasa_config": null,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
+
"qalora_group_size": 16,
|
| 34 |
+
"r": 16,
|
| 35 |
+
"rank_pattern": {},
|
| 36 |
+
"revision": null,
|
| 37 |
+
"target_modules": [
|
| 38 |
+
"out_proj",
|
| 39 |
+
"v_proj",
|
| 40 |
+
"in_proj_qkv",
|
| 41 |
+
"up_proj",
|
| 42 |
+
"in_proj_z",
|
| 43 |
+
"down_proj",
|
| 44 |
+
"gate_proj",
|
| 45 |
+
"o_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
+
"k_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
+
"task_type": null,
|
| 51 |
+
"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
+
"use_dora": false,
|
| 54 |
+
"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1998c229ad01987725960ed3c5763f1da62efb5d123aeb99b59b9792b7010bce
|
| 3 |
+
size 160486456
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
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| 10 |
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| 14 |
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|
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|
| 27 |
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|
| 28 |
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|
| 29 |
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| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
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| 50 |
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|
| 51 |
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|
| 58 |
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|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 176641832
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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| 96 |
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| 97 |
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|
| 99 |
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|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/calibration.json
ADDED
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@@ -0,0 +1,29 @@
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{
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| 28 |
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"source": "models/e33/S1-E33-M20P40-n16k-syn/ckpt-16000"
|
| 29 |
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}
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 393464
|
e33/S1-E33-M20P40-n16k-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
| 1 |
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{
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| 2 |
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|
| 3 |
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|
| 4 |
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| 11 |
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| 17 |
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| 19 |
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| 20 |
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| 21 |
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|
| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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|
| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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| 48 |
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| 49 |
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| 50 |
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| 52 |
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| 60 |
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| 64 |
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| 69 |
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| 71 |
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| 72 |
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| 73 |
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| 74 |
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| 75 |
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|
| 76 |
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| 77 |
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|
| 78 |
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| 79 |
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"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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|
| 81 |
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|
| 82 |
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| 83 |
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| 84 |
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| 89 |
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| 91 |
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| 93 |
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| 94 |
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|
| 95 |
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| 96 |
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| 97 |
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"up_proj",
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| 98 |
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"v_proj"
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| 99 |
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| 100 |
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| 101 |
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| 102 |
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| 103 |
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| 111 |
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| 113 |
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|
| 163 |
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|
| 164 |
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}
|
e33/S1-E33-M20P40-n16k-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
+
{"time": "08:13:07", "event": "start", "data": "data/e33/E33-M20P40-n16k", "data_manifest": {"arm": "E33-M20P40-n16k", "name": null, "train_sha256": "0c998c032f8987adac4577ffcddbc6a65fc3ba6b81ba469c1767c02644b903fb", "n_train": 16000}, "init": "released", "objective": "s-log", "sigma": 0.5, "K": 8, "reward": "brier", "clip": 0.2, "passes": 1, "lr": 0.0001, "lr_head": 0.0002, "rows_per_step": 32, "train_seed": 0, "replay": "data/e16/replay/train.jsonl", "replay_frac": 0.05, "replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e", "max_len": 3072, "schedule": "warmup 0.03 + cosine to x0.05 over 500 steps", "total_rows": 16000, "lora": {"r": 16, "lora_alpha": 32, "lora_dropout": 0.05}, "trainer_sha256": "a0b9d7552588ffb068565686509162a4f122f6f03392e693fa20088493e2a4f3", "device": "cuda", "load_s": 186.75728130340576}
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{"time": "08:24:40", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 848.5050223983193, "loss": 0.7298796325922012, "entropy": 0.6808525398373604, "sharp": 0.06191548611968756}
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| 46 |
+
{"time": "10:55:54", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 822.4939761646747, "loss": 0.6346560120582581, "entropy": 0.6383396536111832, "sharp": 0.1300529083237052}
|
| 47 |
+
{"time": "10:59:44", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 823.1133792883301, "loss": 0.6326565071940422, "entropy": 0.6483790576457977, "sharp": 0.10434569697827101}
|
| 48 |
+
{"time": "11:03:35", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 823.9389462869989, "loss": 0.6603165343403816, "entropy": 0.6323894076049328, "sharp": 0.141101255081594}
|
| 49 |
+
{"time": "11:07:27", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 824.6522983284796, "loss": 0.6576901823282242, "entropy": 0.6554438918828964, "sharp": 0.10777606535702944}
|
| 50 |
+
{"time": "11:11:16", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 825.4080300941106, "loss": 0.6637649387121201, "entropy": 0.6494643464684486, "sharp": 0.12167353462427855}
|
| 51 |
+
{"time": "11:15:02", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 826.0346436111113, "loss": 0.6434320770204067, "entropy": 0.6648931764066219, "sharp": 0.09884033910930157}
|
| 52 |
+
{"time": "11:19:00", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 826.328165731913, "loss": 0.6828350089490414, "entropy": 0.6499973721802235, "sharp": 0.12077272217720747}
|
| 53 |
+
{"time": "11:23:00", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 826.7948135441493, "loss": 0.6283932998776436, "entropy": 0.641958087682724, "sharp": 0.13573688734322786}
|
| 54 |
+
{"time": "11:26:51", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 827.1983496490172, "loss": 0.6231705062091351, "entropy": 0.6532550044357777, "sharp": 0.11139336042106152}
|
| 55 |
+
{"time": "11:30:45", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 827.6767047919681, "loss": 0.6067280508577824, "entropy": 0.6390356905758381, "sharp": 0.14126633014529943}
|
| 56 |
+
{"time": "11:32:14", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5895894765853882, "noul_T": 0.7579464023116482, "noul_auc": 0.737270257042075, "noul_acc": 0.696, "noul_f1": 0.7610062893081762, "noul_nll": 0.5895842367261648, "noul_ece": 0.05830827236175538, "noul_brier": 0.20119680086413858, "noul_sharp": 0.15372470021247864, "entropy": 0.6235913038253784}
|
| 57 |
+
{"time": "11:35:25", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9814579, "tok_per_s": 808.7513072822612, "rows_per_s": 1.3878322760350466, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5733757615089417, "noul_T": 0.7536078969778258, "choice_ce": 0.6717521548271179, "choice_T": 1.0369940375159572, "score_ce": 1.0550035238265991, "score_T": 0.9641858015101192, "noul_auc": 0.7241642666666666, "noul_acc": 0.685, "noul_f1": 0.7608200455580866, "noul_nll": 0.590823968693614, "noul_ece": 0.05668055501580238, "noul_brier": 0.2023056829963619, "noul_sharp": 0.15657421946525574, "entropy": 0.6214356422424316}, "dropped_long": 0, "peak_gib": 18.236003875732422}
|
e33/S1-E33-M40P40-n16k-a100-syn/DONE
ADDED
|
@@ -0,0 +1 @@
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| 1 |
+
2026-10-24 06:50:10
|
e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/README.md
ADDED
|
@@ -0,0 +1,206 @@
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| 1 |
+
---
|
| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
|
| 3 |
+
library_name: peft
|
| 4 |
+
tags:
|
| 5 |
+
- base_model:adapter:/workspace/jev_kt/models/hf/JEV-9B
|
| 6 |
+
- lora
|
| 7 |
+
- transformers
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
# Model Card for Model ID
|
| 11 |
+
|
| 12 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
## Model Details
|
| 17 |
+
|
| 18 |
+
### Model Description
|
| 19 |
+
|
| 20 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
- **Developed by:** [More Information Needed]
|
| 25 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 26 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 27 |
+
- **Model type:** [More Information Needed]
|
| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 29 |
+
- **License:** [More Information Needed]
|
| 30 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 31 |
+
|
| 32 |
+
### Model Sources [optional]
|
| 33 |
+
|
| 34 |
+
<!-- Provide the basic links for the model. -->
|
| 35 |
+
|
| 36 |
+
- **Repository:** [More Information Needed]
|
| 37 |
+
- **Paper [optional]:** [More Information Needed]
|
| 38 |
+
- **Demo [optional]:** [More Information Needed]
|
| 39 |
+
|
| 40 |
+
## Uses
|
| 41 |
+
|
| 42 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 43 |
+
|
| 44 |
+
### Direct Use
|
| 45 |
+
|
| 46 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 47 |
+
|
| 48 |
+
[More Information Needed]
|
| 49 |
+
|
| 50 |
+
### Downstream Use [optional]
|
| 51 |
+
|
| 52 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 53 |
+
|
| 54 |
+
[More Information Needed]
|
| 55 |
+
|
| 56 |
+
### Out-of-Scope Use
|
| 57 |
+
|
| 58 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 59 |
+
|
| 60 |
+
[More Information Needed]
|
| 61 |
+
|
| 62 |
+
## Bias, Risks, and Limitations
|
| 63 |
+
|
| 64 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 65 |
+
|
| 66 |
+
[More Information Needed]
|
| 67 |
+
|
| 68 |
+
### Recommendations
|
| 69 |
+
|
| 70 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 71 |
+
|
| 72 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 73 |
+
|
| 74 |
+
## How to Get Started with the Model
|
| 75 |
+
|
| 76 |
+
Use the code below to get started with the model.
|
| 77 |
+
|
| 78 |
+
[More Information Needed]
|
| 79 |
+
|
| 80 |
+
## Training Details
|
| 81 |
+
|
| 82 |
+
### Training Data
|
| 83 |
+
|
| 84 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 85 |
+
|
| 86 |
+
[More Information Needed]
|
| 87 |
+
|
| 88 |
+
### Training Procedure
|
| 89 |
+
|
| 90 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 91 |
+
|
| 92 |
+
#### Preprocessing [optional]
|
| 93 |
+
|
| 94 |
+
[More Information Needed]
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
#### Training Hyperparameters
|
| 98 |
+
|
| 99 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 100 |
+
|
| 101 |
+
#### Speeds, Sizes, Times [optional]
|
| 102 |
+
|
| 103 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 104 |
+
|
| 105 |
+
[More Information Needed]
|
| 106 |
+
|
| 107 |
+
## Evaluation
|
| 108 |
+
|
| 109 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 110 |
+
|
| 111 |
+
### Testing Data, Factors & Metrics
|
| 112 |
+
|
| 113 |
+
#### Testing Data
|
| 114 |
+
|
| 115 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 116 |
+
|
| 117 |
+
[More Information Needed]
|
| 118 |
+
|
| 119 |
+
#### Factors
|
| 120 |
+
|
| 121 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 122 |
+
|
| 123 |
+
[More Information Needed]
|
| 124 |
+
|
| 125 |
+
#### Metrics
|
| 126 |
+
|
| 127 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 128 |
+
|
| 129 |
+
[More Information Needed]
|
| 130 |
+
|
| 131 |
+
### Results
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
#### Summary
|
| 136 |
+
|
| 137 |
+
|
| 138 |
+
|
| 139 |
+
## Model Examination [optional]
|
| 140 |
+
|
| 141 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 142 |
+
|
| 143 |
+
[More Information Needed]
|
| 144 |
+
|
| 145 |
+
## Environmental Impact
|
| 146 |
+
|
| 147 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 148 |
+
|
| 149 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 150 |
+
|
| 151 |
+
- **Hardware Type:** [More Information Needed]
|
| 152 |
+
- **Hours used:** [More Information Needed]
|
| 153 |
+
- **Cloud Provider:** [More Information Needed]
|
| 154 |
+
- **Compute Region:** [More Information Needed]
|
| 155 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 156 |
+
|
| 157 |
+
## Technical Specifications [optional]
|
| 158 |
+
|
| 159 |
+
### Model Architecture and Objective
|
| 160 |
+
|
| 161 |
+
[More Information Needed]
|
| 162 |
+
|
| 163 |
+
### Compute Infrastructure
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
#### Hardware
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Software
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
## Citation [optional]
|
| 176 |
+
|
| 177 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 178 |
+
|
| 179 |
+
**BibTeX:**
|
| 180 |
+
|
| 181 |
+
[More Information Needed]
|
| 182 |
+
|
| 183 |
+
**APA:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
## Glossary [optional]
|
| 188 |
+
|
| 189 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 190 |
+
|
| 191 |
+
[More Information Needed]
|
| 192 |
+
|
| 193 |
+
## More Information [optional]
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## Model Card Authors [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
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|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
+
"base_model_name_or_path": "/workspace/jev_kt/models/hf/JEV-9B",
|
| 10 |
+
"bias": "none",
|
| 11 |
+
"corda_config": null,
|
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e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter/adapter_model.safetensors
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| 58 |
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e33/S1-E33-M40P40-n16k-a100-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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