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: e45 (0-44)
Browse files- e45/S1-E45-NOISE-ts0-syn/DONE +1 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/README.md +206 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/calibration.json +29 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/head.safetensors +3 -0
- e45/S1-E45-NOISE-ts0-syn/ckpt-16000/judge_config.json +164 -0
- e45/S1-E45-NOISE-ts0-syn/train_log.jsonl +57 -0
- e45/S1-E45-REL-ts0-syn/DONE +1 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter/README.md +206 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/calibration.json +29 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/head.safetensors +3 -0
- e45/S1-E45-REL-ts0-syn/ckpt-16000/judge_config.json +164 -0
- e45/S1-E45-REL-ts0-syn/train_log.jsonl +57 -0
- e45/S1-E45-SHR-ts0-syn/DONE +1 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter/README.md +206 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/calibration.json +29 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/head.safetensors +3 -0
- e45/S1-E45-SHR-ts0-syn/ckpt-16000/judge_config.json +164 -0
- e45/S1-E45-SHR-ts0-syn/train_log.jsonl +57 -0
- e45/S1-E45-SHR-ts1-syn/DONE +1 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter/README.md +206 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter/adapter_config.json +57 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter/adapter_model.safetensors +3 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter_vllm/adapter_config.json +58 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors +3 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter_vllm/decision_head.json +99 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/calibration.json +29 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/head.safetensors +3 -0
- e45/S1-E45-SHR-ts1-syn/ckpt-16000/judge_config.json +164 -0
- e45/S1-E45-SHR-ts1-syn/train_log.jsonl +57 -0
e45/S1-E45-NOISE-ts0-syn/DONE
ADDED
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2026-11-02 01:38:41
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e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/README.md
ADDED
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| 1 |
+
---
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| 2 |
+
base_model: /workspace/jev_kt/models/hf/JEV-9B
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| 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 |
+
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| 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 |
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|
| 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 |
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<!-- 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 |
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[More Information Needed]
|
| 200 |
+
|
| 201 |
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## Model Card Contact
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- PEFT 0.21.2
|
e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/adapter_config.json
ADDED
|
@@ -0,0 +1,57 @@
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| 1 |
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{
|
| 2 |
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"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 |
+
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| 30 |
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| 33 |
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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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"q_proj",
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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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|
e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
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size 160486456
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e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
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@@ -0,0 +1,58 @@
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| 34 |
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| 38 |
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| 39 |
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| 40 |
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| 42 |
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| 45 |
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| 47 |
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],
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| 50 |
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|
e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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size 176641832
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e45/S1-E45-NOISE-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
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| 97 |
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|
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|
e45/S1-E45-NOISE-ts0-syn/ckpt-16000/calibration.json
ADDED
|
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| 28 |
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|
| 29 |
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|
e45/S1-E45-NOISE-ts0-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 393464
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e45/S1-E45-NOISE-ts0-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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| 14 |
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| 20 |
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| 76 |
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| 78 |
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|
e45/S1-E45-NOISE-ts0-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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| 1 |
+
{"time": "22:21:45", "event": "start", "data": "data/e45/E45-NOISE", "data_manifest": {"arm": "E45-NOISE", "name": null, "train_sha256": "53ee5956d8073d8dad59f35016d62ec8cf548a2dec30ffbbe807ee3b8851bb89", "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": 75.91583919525146}
|
| 2 |
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|
| 3 |
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{"time": "22:29:10", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 812.2799692748733, "loss": 0.6161677315831184, "entropy": 0.5316848270595074, "sharp": 0.24935242906212807}
|
| 4 |
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{"time": "22:32:55", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 814.3714298479673, "loss": 0.6004001908004284, "entropy": 0.581790978088975, "sharp": 0.20492732897400856}
|
| 5 |
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{"time": "22:36:34", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 814.9059647678858, "loss": 0.5924058668315411, "entropy": 0.6551112532615662, "sharp": 0.11331460811197758}
|
| 6 |
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{"time": "22:40:20", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 816.5747557678841, "loss": 0.49044235423207283, "entropy": 0.48978979513049126, "sharp": 0.2550374250859022}
|
| 7 |
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{"time": "22:43:58", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 818.0567462637081, "loss": 0.5913941822946072, "entropy": 0.6587455235421658, "sharp": 0.1154701029881835}
|
| 8 |
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{"time": "22:47:43", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 818.0287887770498, "loss": 0.5806628204882145, "entropy": 0.5434654653072357, "sharp": 0.2351485677063465}
|
| 9 |
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{"time": "22:51:24", "event": "step", "step": 80, "rows_seen": 2560, "lr": 9.585159297207315e-05, "tok_per_s": 817.8545281189062, "loss": 0.6320503326132894, "entropy": 0.6085324361920357, "sharp": 0.17389390245079994}
|
| 10 |
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{"time": "22:55:12", "event": "step", "step": 90, "rows_seen": 2880, "lr": 9.450403580967612e-05, "tok_per_s": 819.0848385824808, "loss": 0.6345171425491571, "entropy": 0.5344767961651087, "sharp": 0.23385817371308804}
|
| 11 |
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{"time": "22:58:57", "event": "step", "step": 100, "rows_seen": 3200, "lr": 9.298029912365855e-05, "tok_per_s": 818.6446398429629, "loss": 0.5553547888994217, "entropy": 0.6228579804301262, "sharp": 0.16205373965203762}
|
| 12 |
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|
| 13 |
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{"time": "23:04:06", "event": "step", "step": 110, "rows_seen": 3520, "lr": 9.128677399521752e-05, "tok_per_s": 790.351410354805, "loss": 0.6075951606035233, "entropy": 0.5805092714726925, "sharp": 0.19646665640175343}
|
| 14 |
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{"time": "23:08:00", "event": "step", "step": 120, "rows_seen": 3840, "lr": 8.943056365728335e-05, "tok_per_s": 793.5821388629806, "loss": 0.5906296093016863, "entropy": 0.5608868785202503, "sharp": 0.2055661454796791}
|
| 15 |
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{"time": "23:11:51", "event": "step", "step": 130, "rows_seen": 4160, "lr": 8.741945370109202e-05, "tok_per_s": 796.4268035701265, "loss": 0.5829800367355347, "entropy": 0.5096677727997303, "sharp": 0.2565692625939846}
|
| 16 |
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|
| 17 |
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{"time": "23:19:22", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 799.2394784968031, "loss": 0.66122030839324, "entropy": 0.6240631230175495, "sharp": 0.14638944528996944}
|
| 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": "23:39:21", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.5714945197105408, "noul_T": 0.8396485132267894, "noul_auc": 0.7467722063762637, "noul_acc": 0.69, "noul_f1": 0.7683109118086696, "noul_nll": 0.5749939913153649, "noul_ece": 0.06094935488700867, "noul_brier": 0.19602544412931885, "noul_sharp": 0.18119440972805023, "entropy": 0.5985406041145325}
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{"time": "23:43:08", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 791.176478771693, "loss": 0.5447567291557789, "entropy": 0.5726124010980129, "sharp": 0.21290836110711098}
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| 25 |
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|
| 26 |
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{"time": "23:50:22", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 793.4351311439757, "loss": 0.5559693370014429, "entropy": 0.5679895356297493, "sharp": 0.22135603800415993}
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| 27 |
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| 31 |
+
{"time": "00:08:50", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 797.6053623369786, "loss": 0.6085697417147458, "entropy": 0.5505957510322332, "sharp": 0.22415123693645}
|
| 32 |
+
{"time": "00:12:37", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 798.4635199283907, "loss": 0.6016140468418598, "entropy": 0.5419358648359776, "sharp": 0.2187774581834674}
|
| 33 |
+
{"time": "00:16:21", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 799.4145723541988, "loss": 0.5394259113818407, "entropy": 0.5766057875007391, "sharp": 0.1751016043126583}
|
| 34 |
+
{"time": "00:17:51", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5705423951148987, "noul_T": 0.7897022029325768, "noul_auc": 0.7468903478422304, "noul_acc": 0.69, "noul_f1": 0.7566718995290423, "noul_nll": 0.57470042078197, "noul_ece": 0.048341548919677735, "noul_brier": 0.1965242978512345, "noul_sharp": 0.16892224550247192, "entropy": 0.6030024886131287}
|
| 35 |
+
{"time": "00:21:26", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 790.0398472234662, "loss": 0.5552126560360193, "entropy": 0.590318825095892, "sharp": 0.17391379363834858}
|
| 36 |
+
{"time": "00:24:58", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 790.595842243345, "loss": 0.6531740333884954, "entropy": 0.5938975121825933, "sharp": 0.1760867815464735}
|
| 37 |
+
{"time": "00:28:40", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 791.5601330906195, "loss": 0.5646311268210411, "entropy": 0.5547943003475666, "sharp": 0.2204857561737299}
|
| 38 |
+
{"time": "00:32:21", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 792.3643918584958, "loss": 0.6441864799708128, "entropy": 0.6056978944689035, "sharp": 0.1601609317585826}
|
| 39 |
+
{"time": "00:35:56", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 792.9287138547262, "loss": 0.6113428547978401, "entropy": 0.6029693968594074, "sharp": 0.16428233589977026}
|
| 40 |
+
{"time": "00:39:35", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 793.8067028556798, "loss": 0.6038871817290783, "entropy": 0.6176639050245285, "sharp": 0.16306819207966328}
|
| 41 |
+
{"time": "00:43:12", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 794.7055557632381, "loss": 0.6174044692888856, "entropy": 0.5644715474918485, "sharp": 0.21021682769060135}
|
| 42 |
+
{"time": "00:47:01", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 795.4030562943802, "loss": 0.5908838883042336, "entropy": 0.578949835151434, "sharp": 0.18708872236311436}
|
| 43 |
+
{"time": "00:50:49", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 796.3470878647198, "loss": 0.6300652399659157, "entropy": 0.5999844558537006, "sharp": 0.15865095611661673}
|
| 44 |
+
{"time": "00:54:25", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 796.6771601277901, "loss": 0.5785091854631901, "entropy": 0.5944705307483673, "sharp": 0.17086115293204784}
|
| 45 |
+
{"time": "00:55:55", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5688287615776062, "noul_T": 0.9422926574527882, "noul_auc": 0.7455907917165954, "noul_acc": 0.702, "noul_f1": 0.7738998482549317, "noul_nll": 0.5742071931585669, "noul_ece": 0.03983503699302675, "noul_brier": 0.19655492965359214, "noul_sharp": 0.18843500316143036, "entropy": 0.5780614018440247}
|
| 46 |
+
{"time": "00:59:36", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 789.4412731587039, "loss": 0.6104978807270527, "entropy": 0.5868110209703445, "sharp": 0.18706927634775639}
|
| 47 |
+
{"time": "01:03:06", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 789.9833813177559, "loss": 0.6568277468904853, "entropy": 0.6150003271177411, "sharp": 0.15597743541002274}
|
| 48 |
+
{"time": "01:06:53", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 790.6631990684843, "loss": 0.5819298066198826, "entropy": 0.5761610679328442, "sharp": 0.1879867846146226}
|
| 49 |
+
{"time": "01:10:27", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 791.3829024839538, "loss": 0.5931172147393227, "entropy": 0.5953016579151154, "sharp": 0.17613293882459402}
|
| 50 |
+
{"time": "01:14:18", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 791.9936980330433, "loss": 0.5529641471803188, "entropy": 0.5828006211668253, "sharp": 0.19747456163167953}
|
| 51 |
+
{"time": "01:17:49", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 792.5522837484663, "loss": 0.586802514269948, "entropy": 0.5967636238783598, "sharp": 0.18801777809858322}
|
| 52 |
+
{"time": "01:21:22", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 793.1638712068302, "loss": 0.5895590409636497, "entropy": 0.5700822174549103, "sharp": 0.2148651648312807}
|
| 53 |
+
{"time": "01:25:11", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 793.8580780830048, "loss": 0.5889317747205496, "entropy": 0.5603284165263176, "sharp": 0.2201318647712469}
|
| 54 |
+
{"time": "01:28:58", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 794.4824516676765, "loss": 0.6158607490360737, "entropy": 0.5687417462468147, "sharp": 0.19970327615737915}
|
| 55 |
+
{"time": "01:32:49", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 794.9774856811176, "loss": 0.5487720184028149, "entropy": 0.5344221629202366, "sharp": 0.23927496001124382}
|
| 56 |
+
{"time": "01:34:19", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5672667026519775, "noul_T": 0.9176552540260776, "noul_auc": 0.7497763750822771, "noul_acc": 0.71, "noul_f1": 0.7730829420970265, "noul_nll": 0.5704260485731065, "noul_ece": 0.044484161734580994, "noul_brier": 0.1950136731050071, "noul_sharp": 0.18746744096279144, "entropy": 0.5805526375770569}
|
| 57 |
+
{"time": "01:38:41", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9113478, "tok_per_s": 775.9031187478307, "rows_per_s": 1.4338938789175861, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5531377196311951, "noul_T": 0.8911908555798087, "choice_ce": 0.6708876490592957, "choice_T": 1.0220903707073858, "score_ce": 1.0566658973693848, "score_T": 0.9871672059187314, "noul_auc": 0.7480106666666667, "noul_acc": 0.709, "noul_f1": 0.781038374717833, "noul_nll": 0.5666926582697779, "noul_ece": 0.03606485928595067, "noul_brier": 0.1934133365102207, "noul_sharp": 0.18925884366035461, "entropy": 0.5806081295013428}, "dropped_long": 0, "peak_gib": 18.237416744232178}
|
e45/S1-E45-REL-ts0-syn/DONE
ADDED
|
@@ -0,0 +1 @@
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| 1 |
+
2026-11-01 20:14:41
|
e45/S1-E45-REL-ts0-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
|
e45/S1-E45-REL-ts0-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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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
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"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 |
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|
| 12 |
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|
| 13 |
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"eva_config": null,
|
| 14 |
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"exclude_modules": null,
|
| 15 |
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"fan_in_fan_out": false,
|
| 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 |
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"layer_replication": null,
|
| 20 |
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"layers_pattern": null,
|
| 21 |
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"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
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"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 |
+
"v_proj",
|
| 39 |
+
"down_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"o_proj",
|
| 42 |
+
"k_proj",
|
| 43 |
+
"in_proj_qkv",
|
| 44 |
+
"up_proj",
|
| 45 |
+
"in_proj_z",
|
| 46 |
+
"out_proj",
|
| 47 |
+
"gate_proj"
|
| 48 |
+
],
|
| 49 |
+
"target_parameters": null,
|
| 50 |
+
"task_type": null,
|
| 51 |
+
"trainable_token_indices": null,
|
| 52 |
+
"use_bdlora": null,
|
| 53 |
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"use_dora": false,
|
| 54 |
+
"use_qalora": false,
|
| 55 |
+
"use_rslora": false,
|
| 56 |
+
"velora_config": null
|
| 57 |
+
}
|
e45/S1-E45-REL-ts0-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 |
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oid sha256:2f7b0ac1f4c0e3d168a2531a32e417927d52c0ebe854408e2476239968a5ec93
|
| 3 |
+
size 160486456
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
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|
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|
| 1 |
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{
|
| 2 |
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"alora_invocation_tokens": null,
|
| 3 |
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"alpha_pattern": {},
|
| 4 |
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"arrow_config": null,
|
| 5 |
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"auto_mapping": {
|
| 6 |
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"base_model_class": "Qwen3_5ForCausalLM",
|
| 7 |
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"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
|
| 8 |
+
},
|
| 9 |
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"base_model_name_or_path": null,
|
| 10 |
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"bias": "none",
|
| 11 |
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|
| 12 |
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|
| 13 |
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"eva_config": null,
|
| 14 |
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|
| 15 |
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"fan_in_fan_out": false,
|
| 16 |
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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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"lora_alpha": 64.0,
|
| 24 |
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|
| 25 |
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"lora_dropout": 0.0,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
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|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
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|
| 30 |
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"monteclora_config": null,
|
| 31 |
+
"peft_type": "LORA",
|
| 32 |
+
"peft_version": "0.21.0",
|
| 33 |
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"qalora_group_size": 16,
|
| 34 |
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"r": 32,
|
| 35 |
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|
| 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 |
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"task_type": null,
|
| 52 |
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"trainable_token_indices": null,
|
| 53 |
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|
| 54 |
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|
| 55 |
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"use_qalora": false,
|
| 56 |
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"use_rslora": false,
|
| 57 |
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"velora_config": null
|
| 58 |
+
}
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
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|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:b1f2e506f8718798fa5beb112d2b40c79215ba7fd5142cdb6fa8d7857ccce73c
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| 3 |
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size 176641832
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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45,
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47
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|
| 55 |
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|
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| 57 |
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| 58 |
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0,
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"verbalizers": [
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| 71 |
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"true",
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| 73 |
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| 74 |
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|
| 75 |
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| 76 |
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|
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| 78 |
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| 80 |
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|
| 81 |
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|
| 82 |
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"D",
|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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| 87 |
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"I",
|
| 88 |
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| 89 |
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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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"template_version": "bare-v1"
|
| 97 |
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},
|
| 98 |
+
"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
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|
| 1 |
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{
|
| 2 |
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"version": 1,
|
| 3 |
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"per_kind": {
|
| 4 |
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"noul": 0.8986131205248705,
|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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"n": 1087,
|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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"choice": {
|
| 16 |
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"n": 60,
|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
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"score": {
|
| 22 |
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|
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|
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|
| 25 |
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|
| 27 |
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|
| 28 |
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"source": "models/e45/S1-E45-REL-ts0-syn/ckpt-16000"
|
| 29 |
+
}
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/head.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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oid sha256:586c28467b1ef73bd4e025e3e7d583501e9161c74110243696bca571f7d771e0
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| 3 |
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size 393464
|
e45/S1-E45-REL-ts0-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
| 1 |
+
{
|
| 2 |
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|
| 3 |
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|
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|
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| 16 |
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| 18 |
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| 19 |
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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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|
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|
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| 70 |
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|
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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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|
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|
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|
| 84 |
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|
e45/S1-E45-REL-ts0-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
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|
| 1 |
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{"time": "16:58:01", "event": "start", "data": "data/e45/E45-REL", "data_manifest": {"arm": "E45-REL", "name": null, "train_sha256": "9b28e9361099b0a8af4abb1ca5a7de90044f7952fc15ff52b8b48740865e2d11", "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": 87.95106148719788}
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| 2 |
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{"time": "17:01:46", "event": "step", "step": 10, "rows_seen": 320, "lr": 7.333333333333333e-05, "tok_per_s": 807.2548328173016, "loss": 0.5859159016981721, "entropy": 0.5220357663929462, "sharp": 0.2621446754783392}
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| 3 |
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{"time": "17:05:31", "event": "step", "step": 20, "rows_seen": 640, "lr": 9.997508952966197e-05, "tok_per_s": 810.3049407408063, "loss": 0.609489593654871, "entropy": 0.5048594251275063, "sharp": 0.27302069775760174}
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| 4 |
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{"time": "17:09:18", "event": "step", "step": 30, "rows_seen": 960, "lr": 9.977596250541417e-05, "tok_per_s": 812.0906100819824, "loss": 0.6011982820928097, "entropy": 0.5863940715789795, "sharp": 0.2008225740864873}
|
| 5 |
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{"time": "17:12:59", "event": "step", "step": 40, "rows_seen": 1280, "lr": 9.937854366485982e-05, "tok_per_s": 813.511917834499, "loss": 0.5325711295008659, "entropy": 0.5941349901258945, "sharp": 0.19071562588214874}
|
| 6 |
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{"time": "17:16:47", "event": "step", "step": 50, "rows_seen": 1600, "lr": 9.8784499920729e-05, "tok_per_s": 814.9273939064152, "loss": 0.5196209773421288, "entropy": 0.5497458279132843, "sharp": 0.22399818152189255}
|
| 7 |
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{"time": "17:20:28", "event": "step", "step": 60, "rows_seen": 1920, "lr": 9.79963228989294e-05, "tok_per_s": 816.1146020410687, "loss": 0.5912675000727177, "entropy": 0.6419856585562229, "sharp": 0.13590564485639334}
|
| 8 |
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{"time": "17:24:14", "event": "step", "step": 70, "rows_seen": 2240, "lr": 9.701731848780134e-05, "tok_per_s": 816.2519339620111, "loss": 0.5597155205905437, "entropy": 0.602167870849371, "sharp": 0.17172034922987223}
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| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
+
{"time": "17:52:16", "event": "step", "step": 140, "rows_seen": 4480, "lr": 8.526187942070997e-05, "tok_per_s": 797.5907036110415, "loss": 0.588726045563817, "entropy": 0.5915715508162975, "sharp": 0.18919290602207184}
|
| 17 |
+
{"time": "17:56:04", "event": "step", "step": 150, "rows_seen": 4800, "lr": 8.296689043247915e-05, "tok_per_s": 799.081284836039, "loss": 0.6570097580552101, "entropy": 0.6380404345691204, "sharp": 0.14082889910787344}
|
| 18 |
+
{"time": "17:59:43", "event": "step", "step": 160, "rows_seen": 5120, "lr": 8.054411271778132e-05, "tok_per_s": 800.4618488199133, "loss": 0.6297760903835297, "entropy": 0.5893573388457298, "sharp": 0.17969845049083233}
|
| 19 |
+
{"time": "18:03:30", "event": "step", "step": 170, "rows_seen": 5440, "lr": 7.800370824832674e-05, "tok_per_s": 801.7603733005637, "loss": 0.5962249897420406, "entropy": 0.5910500138998032, "sharp": 0.1914851674810052}
|
| 20 |
+
{"time": "18:07:13", "event": "step", "step": 180, "rows_seen": 5760, "lr": 7.535633236331324e-05, "tok_per_s": 803.0116347975378, "loss": 0.5863769315183163, "entropy": 0.617675743997097, "sharp": 0.15867283195257187}
|
| 21 |
+
{"time": "18:10:58", "event": "step", "step": 190, "rows_seen": 6080, "lr": 7.26130890772308e-05, "tok_per_s": 803.684088102376, "loss": 0.6129954941570759, "entropy": 0.5540583729743958, "sharp": 0.2156384475529194}
|
| 22 |
+
{"time": "18:14:42", "event": "step", "step": 200, "rows_seen": 6400, "lr": 6.978548450576568e-05, "tok_per_s": 804.754047443891, "loss": 0.5601796135306358, "entropy": 0.573649849742651, "sharp": 0.21057562343776226}
|
| 23 |
+
{"time": "18:16:12", "event": "val", "step": 200, "rows_seen": 6400, "n": 500, "dropped_long": 0, "noul_ce": 0.5716017484664917, "noul_T": 0.892537978095737, "noul_auc": 0.7445106411706132, "noul_acc": 0.678, "noul_f1": 0.7670043415340086, "noul_nll": 0.5777599147334694, "noul_ece": 0.055663657426834115, "noul_brier": 0.19777273337476287, "noul_sharp": 0.18703073263168335, "entropy": 0.5899770259857178}
|
| 24 |
+
{"time": "18:20:00", "event": "step", "step": 210, "rows_seen": 6720, "lr": 6.688537860515266e-05, "tok_per_s": 791.0806056266221, "loss": 0.5494696125388145, "entropy": 0.5707839652895927, "sharp": 0.20891448017209768}
|
| 25 |
+
{"time": "18:23:39", "event": "step", "step": 220, "rows_seen": 7040, "lr": 6.392493542739706e-05, "tok_per_s": 792.4182634401858, "loss": 0.600819818675518, "entropy": 0.5623787865042686, "sharp": 0.2135008368641138}
|
| 26 |
+
{"time": "18:27:15", "event": "step", "step": 230, "rows_seen": 7360, "lr": 6.091657210001309e-05, "tok_per_s": 793.5993626890156, "loss": 0.5575203914195299, "entropy": 0.564382541924715, "sharp": 0.22327942494302988}
|
| 27 |
+
{"time": "18:30:56", "event": "step", "step": 240, "rows_seen": 7680, "lr": 5.7872906744276015e-05, "tok_per_s": 794.7269218728223, "loss": 0.564826387912035, "entropy": 0.5365338232368231, "sharp": 0.2335683573037386}
|
| 28 |
+
{"time": "18:34:54", "event": "step", "step": 250, "rows_seen": 8000, "lr": 5.48067055504363e-05, "tok_per_s": 795.6100957928961, "loss": 0.5920643508434296, "entropy": 0.5942213386297226, "sharp": 0.18172888085246086}
|
| 29 |
+
{"time": "18:38:23", "event": "step", "step": 260, "rows_seen": 8320, "lr": 5.173082923188119e-05, "tok_per_s": 796.5723098643724, "loss": 0.5873812437057495, "entropy": 0.5533143579959869, "sharp": 0.20813973061740398}
|
| 30 |
+
{"time": "18:42:06", "event": "step", "step": 270, "rows_seen": 8640, "lr": 4.865817908283331e-05, "tok_per_s": 797.4336521718462, "loss": 0.6422621437814087, "entropy": 0.6008757147938013, "sharp": 0.1711443830281496}
|
| 31 |
+
{"time": "18:45:48", "event": "step", "step": 280, "rows_seen": 8960, "lr": 4.560164286583922e-05, "tok_per_s": 798.2961361537441, "loss": 0.605023676995188, "entropy": 0.5507638463750482, "sharp": 0.22286107577383518}
|
| 32 |
+
{"time": "18:49:35", "event": "step", "step": 290, "rows_seen": 9280, "lr": 4.257404075601443e-05, "tok_per_s": 799.2073680368666, "loss": 0.6119903288781643, "entropy": 0.5475618652999401, "sharp": 0.21826686710119247}
|
| 33 |
+
{"time": "18:53:21", "event": "step", "step": 300, "rows_seen": 9600, "lr": 3.958807156877371e-05, "tok_per_s": 800.1413526371964, "loss": 0.5355819761753082, "entropy": 0.5809243451803923, "sharp": 0.16378754749894142}
|
| 34 |
+
{"time": "18:54:51", "event": "val", "step": 300, "rows_seen": 9600, "n": 500, "dropped_long": 0, "noul_ce": 0.5724663138389587, "noul_T": 0.7306648195462849, "noul_auc": 0.745303876727819, "noul_acc": 0.694, "noul_f1": 0.7598116169544741, "noul_nll": 0.5765132632516324, "noul_ece": 0.05441170465946198, "noul_brier": 0.19739392816312815, "noul_sharp": 0.1575111746788025, "entropy": 0.6112444400787354}
|
| 35 |
+
{"time": "18:58:28", "event": "step", "step": 310, "rows_seen": 9920, "lr": 3.665625949658603e-05, "tok_per_s": 790.7888034789369, "loss": 0.5504805911332369, "entropy": 0.5683636218309402, "sharp": 0.1921995673328638}
|
| 36 |
+
{"time": "19:01:59", "event": "step", "step": 320, "rows_seen": 10240, "lr": 3.379090157815887e-05, "tok_per_s": 791.5357089546385, "loss": 0.6405128911137581, "entropy": 0.6108909472823143, "sharp": 0.16367854736745358}
|
| 37 |
+
{"time": "19:05:40", "event": "step", "step": 330, "rows_seen": 10560, "lr": 3.10040161203844e-05, "tok_per_s": 792.7184778788117, "loss": 0.5662273876369, "entropy": 0.5532629452645779, "sharp": 0.22433722764253616}
|
| 38 |
+
{"time": "19:09:22", "event": "step", "step": 340, "rows_seen": 10880, "lr": 2.8307292289383776e-05, "tok_per_s": 793.6153484783152, "loss": 0.6378334686160088, "entropy": 0.6033659428358078, "sharp": 0.16770764626562595}
|
| 39 |
+
{"time": "19:12:55", "event": "step", "step": 350, "rows_seen": 11200, "lr": 2.571204108208194e-05, "tok_per_s": 794.3910734803789, "loss": 0.6115953102707863, "entropy": 0.5891885012388229, "sharp": 0.17483517061918974}
|
| 40 |
+
{"time": "19:16:36", "event": "step", "step": 360, "rows_seen": 11520, "lr": 2.322914788395595e-05, "tok_per_s": 795.2063749867742, "loss": 0.605057317763567, "entropy": 0.6163841933012009, "sharp": 0.165567209944129}
|
| 41 |
+
{"time": "19:20:15", "event": "step", "step": 370, "rows_seen": 11840, "lr": 2.0869026811945157e-05, "tok_per_s": 796.1282829075584, "loss": 0.6140534365549684, "entropy": 0.5582990748807788, "sharp": 0.21383531764149666}
|
| 42 |
+
{"time": "19:24:05", "event": "step", "step": 380, "rows_seen": 12160, "lr": 1.8641577034025627e-05, "tok_per_s": 796.7956926983873, "loss": 0.5914619974792004, "entropy": 0.5759841613471508, "sharp": 0.18765570037066936}
|
| 43 |
+
{"time": "19:27:55", "event": "step", "step": 390, "rows_seen": 12480, "lr": 1.6556141248659472e-05, "tok_per_s": 797.7675759292986, "loss": 0.6305775959044695, "entropy": 0.598133459687233, "sharp": 0.16215836256742477}
|
| 44 |
+
{"time": "19:31:30", "event": "step", "step": 400, "rows_seen": 12800, "lr": 1.4621466498270773e-05, "tok_per_s": 798.2436605927263, "loss": 0.5794996656477451, "entropy": 0.5955066867172718, "sharp": 0.16796090174466372}
|
| 45 |
+
{"time": "19:33:00", "event": "val", "step": 400, "rows_seen": 12800, "n": 500, "dropped_long": 0, "noul_ce": 0.5678415894508362, "noul_T": 0.9189865268481029, "noul_auc": 0.7460296028759008, "noul_acc": 0.704, "noul_f1": 0.7757575757575758, "noul_nll": 0.572774373812601, "noul_ece": 0.051562166929245, "noul_brier": 0.1962206297461335, "noul_sharp": 0.18654365837574005, "entropy": 0.5807515382766724}
|
| 46 |
+
{"time": "19:36:39", "event": "step", "step": 410, "rows_seen": 13120, "lr": 1.284566748110963e-05, "tok_per_s": 791.2294968832349, "loss": 0.5959222391247749, "entropy": 0.5914434641599655, "sharp": 0.18311581946909428}
|
| 47 |
+
{"time": "19:40:11", "event": "step", "step": 420, "rows_seen": 13440, "lr": 1.1236192515387821e-05, "tok_per_s": 791.7543976296596, "loss": 0.6583403283730149, "entropy": 0.6149237090721726, "sharp": 0.1567009538412094}
|
| 48 |
+
{"time": "19:43:58", "event": "step", "step": 430, "rows_seen": 13760, "lr": 9.799792298443728e-06, "tok_per_s": 792.4833429908712, "loss": 0.5807589301839471, "entropy": 0.5776796638965607, "sharp": 0.18376952782273293}
|
| 49 |
+
{"time": "19:47:34", "event": "step", "step": 440, "rows_seen": 14080, "lr": 8.542491591971554e-06, "tok_per_s": 793.2114579870419, "loss": 0.5974132008850574, "entropy": 0.5908592492341995, "sharp": 0.17492880299687386}
|
| 50 |
+
{"time": "19:51:25", "event": "step", "step": 450, "rows_seen": 14400, "lr": 7.469563952077155e-06, "tok_per_s": 793.8329637937026, "loss": 0.5518267657607794, "entropy": 0.5826755538582802, "sharp": 0.19769825227558613}
|
| 51 |
+
{"time": "19:54:57", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 794.4148421853414, "loss": 0.5820136964321136, "entropy": 0.5885909758508205, "sharp": 0.19301331602036953}
|
| 52 |
+
{"time": "19:58:30", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 795.0769700161079, "loss": 0.5867369882762432, "entropy": 0.5726926028728485, "sharp": 0.21091781370341778}
|
| 53 |
+
{"time": "20:02:21", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 795.7072370840369, "loss": 0.5849715080112219, "entropy": 0.5596798043698072, "sharp": 0.217598307877779}
|
| 54 |
+
{"time": "20:06:09", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 796.336443990316, "loss": 0.6060212701559067, "entropy": 0.5702655911445618, "sharp": 0.20112621411681175}
|
| 55 |
+
{"time": "20:09:58", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 797.0595319298499, "loss": 0.548908244818449, "entropy": 0.5237538851797581, "sharp": 0.24975336156785488}
|
| 56 |
+
{"time": "20:11:28", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5660662651062012, "noul_T": 0.9170049092020095, "noul_auc": 0.7498607618436821, "noul_acc": 0.698, "noul_f1": 0.7666151468315301, "noul_nll": 0.5690367848649621, "noul_ece": 0.03417138195037843, "noul_brier": 0.19473311058885026, "noul_sharp": 0.18767905235290527, "entropy": 0.5794568061828613}
|
| 57 |
+
{"time": "20:14:41", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9179126, "tok_per_s": 778.0060240998838, "rows_per_s": 1.4274972858277077, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5520605444908142, "noul_T": 0.8986131205248705, "choice_ce": 0.6677042245864868, "choice_T": 0.9752874633489123, "score_ce": 1.0668580532073975, "score_T": 0.9821101673825277, "noul_auc": 0.7464661333333333, "noul_acc": 0.706, "noul_f1": 0.7805970149253731, "noul_nll": 0.5664093009401113, "noul_ece": 0.026353577703237534, "noul_brier": 0.1935194658173043, "noul_sharp": 0.1905725747346878, "entropy": 0.5781111121177673}, "dropped_long": 0, "peak_gib": 18.237416744232178}
|
e45/S1-E45-SHR-ts0-syn/DONE
ADDED
|
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| 1 |
+
2026-11-01 14:56:35
|
e45/S1-E45-SHR-ts0-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
|
e45/S1-E45-SHR-ts0-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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|
|
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|
|
|
|
|
|
|
|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
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"auto_mapping": {
|
| 6 |
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"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 |
+
"v_proj",
|
| 39 |
+
"q_proj",
|
| 40 |
+
"o_proj",
|
| 41 |
+
"down_proj",
|
| 42 |
+
"in_proj_z",
|
| 43 |
+
"gate_proj",
|
| 44 |
+
"out_proj",
|
| 45 |
+
"in_proj_qkv",
|
| 46 |
+
"k_proj",
|
| 47 |
+
"up_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 |
+
}
|
e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:368bf46a30363310c7fab7fe435292781edfe7b76a0ba184633be79ab6ab390b
|
| 3 |
+
size 160486456
|
e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter_vllm/adapter_config.json
ADDED
|
@@ -0,0 +1,58 @@
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{
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| 7 |
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|
| 8 |
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},
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|
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| 29 |
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| 30 |
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"monteclora_config": null,
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| 31 |
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"peft_type": "LORA",
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| 33 |
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|
| 34 |
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"r": 32,
|
| 35 |
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| 36 |
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| 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 |
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"v_proj"
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],
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"velora_config": null
|
| 58 |
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}
|
e45/S1-E45-SHR-ts0-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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size 176641832
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e45/S1-E45-SHR-ts0-syn/ckpt-16000/adapter_vllm/decision_head.json
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| 19 |
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|
| 20 |
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-0.004388121422380209,
|
| 21 |
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|
| 22 |
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| 23 |
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|
| 24 |
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-0.0034523631911724806,
|
| 25 |
+
-0.005643394310027361,
|
| 26 |
+
-0.0035082357935607433
|
| 27 |
+
],
|
| 28 |
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"verbalizer_ids": [
|
| 29 |
+
3721,
|
| 30 |
+
1802,
|
| 31 |
+
15,
|
| 32 |
+
16,
|
| 33 |
+
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 |
+
],
|
| 54 |
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"slots": {
|
| 55 |
+
"num_slots": 24,
|
| 56 |
+
"ranges": {
|
| 57 |
+
"noul": [
|
| 58 |
+
0,
|
| 59 |
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2
|
| 60 |
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],
|
| 61 |
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"score": [
|
| 62 |
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2,
|
| 63 |
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8
|
| 64 |
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],
|
| 65 |
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"choice": [
|
| 66 |
+
8,
|
| 67 |
+
24
|
| 68 |
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]
|
| 69 |
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},
|
| 70 |
+
"verbalizers": [
|
| 71 |
+
"false",
|
| 72 |
+
"true",
|
| 73 |
+
"0",
|
| 74 |
+
"1",
|
| 75 |
+
"2",
|
| 76 |
+
"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 |
+
}
|
e45/S1-E45-SHR-ts0-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"version": 1,
|
| 3 |
+
"per_kind": {
|
| 4 |
+
"noul": 0.9000755854451329,
|
| 5 |
+
"choice": 1.008406819192068,
|
| 6 |
+
"score": 0.9500376826602371
|
| 7 |
+
},
|
| 8 |
+
"fit": {
|
| 9 |
+
"noul": {
|
| 10 |
+
"n": 1087,
|
| 11 |
+
"T": 0.9000755854451329,
|
| 12 |
+
"ce_before": 0.5519391894340515,
|
| 13 |
+
"ce_after": 0.5510237812995911
|
| 14 |
+
},
|
| 15 |
+
"choice": {
|
| 16 |
+
"n": 60,
|
| 17 |
+
"T": 1.008406819192068,
|
| 18 |
+
"ce_before": 0.6665812730789185,
|
| 19 |
+
"ce_after": 0.6665658354759216
|
| 20 |
+
},
|
| 21 |
+
"score": {
|
| 22 |
+
"n": 53,
|
| 23 |
+
"T": 0.9500376826602371,
|
| 24 |
+
"ce_before": 1.0586308240890503,
|
| 25 |
+
"ce_after": 1.057839274406433
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"source": "models/e45/S1-E45-SHR-ts0-syn/ckpt-16000"
|
| 29 |
+
}
|
e45/S1-E45-SHR-ts0-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:a8a1c5e546d378f027a69a13f4e1aa7d02b9c409613ecb1ba9fb82ef2b62a061
|
| 3 |
+
size 393464
|
e45/S1-E45-SHR-ts0-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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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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 |
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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 |
+
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|
| 50 |
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|
| 51 |
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|
| 52 |
+
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|
| 53 |
+
17,
|
| 54 |
+
18,
|
| 55 |
+
19,
|
| 56 |
+
20,
|
| 57 |
+
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|
| 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 |
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"kinds": [
|
| 75 |
+
"noul",
|
| 76 |
+
"choice",
|
| 77 |
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"score"
|
| 78 |
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],
|
| 79 |
+
"model_name": "jev-judge-qwen35-9b",
|
| 80 |
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"model_version": "0.8.0",
|
| 81 |
+
"lm_head_included": true,
|
| 82 |
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"weights_mode": "unmerged",
|
| 83 |
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"adapter_subfolder": "adapter",
|
| 84 |
+
"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 |
+
"gate_proj",
|
| 91 |
+
"in_proj_qkv",
|
| 92 |
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"in_proj_z",
|
| 93 |
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"k_proj",
|
| 94 |
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"o_proj",
|
| 95 |
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"out_proj",
|
| 96 |
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"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/e45/S1-E45-SHR-ts0-syn/ckpt-16000",
|
| 103 |
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"softcap": null,
|
| 104 |
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"e16": {
|
| 105 |
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"data": "data/e45/E45-SHR",
|
| 106 |
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"data_manifest": {
|
| 107 |
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"arm": "E45-SHR",
|
| 108 |
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"name": null,
|
| 109 |
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"n_train": 16000
|
| 111 |
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},
|
| 112 |
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"init": "released",
|
| 113 |
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|
| 114 |
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"sigma": 0.5,
|
| 115 |
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"K": 8,
|
| 116 |
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|
| 117 |
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|
| 118 |
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|
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|
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|
| 121 |
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|
| 122 |
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|
| 123 |
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"replay": "data/e16/replay/train.jsonl",
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"replay_sha256": "9dd2df19851678750cf79d2fdb47581720930ef2f0c6e18e6fbe23ef2181847e",
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|
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
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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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"step": 500,
|
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"tokens": 9113125,
|
| 141 |
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|
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|
| 143 |
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"val": {
|
| 144 |
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"n": 1200,
|
| 145 |
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|
| 146 |
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|
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|
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|
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"choice_T": 1.008406819192068,
|
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"score_ce": 1.0586308240890503,
|
| 151 |
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"score_T": 0.9500376826602371,
|
| 152 |
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"noul_auc": 0.7466709333333332,
|
| 153 |
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"noul_acc": 0.702,
|
| 154 |
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"noul_f1": 0.7776119402985074,
|
| 155 |
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"noul_nll": 0.5664786969861015,
|
| 156 |
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|
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"entropy": 0.5782209038734436
|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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}
|
| 164 |
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}
|
e45/S1-E45-SHR-ts0-syn/train_log.jsonl
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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| 57 |
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e45/S1-E45-SHR-ts1-syn/DONE
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e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter/README.md
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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
|
e45/S1-E45-SHR-ts1-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 |
+
"k_proj",
|
| 39 |
+
"q_proj",
|
| 40 |
+
"o_proj",
|
| 41 |
+
"out_proj",
|
| 42 |
+
"v_proj",
|
| 43 |
+
"down_proj",
|
| 44 |
+
"in_proj_z",
|
| 45 |
+
"in_proj_qkv",
|
| 46 |
+
"gate_proj",
|
| 47 |
+
"up_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 |
+
}
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:82c36a64467a886a65c667e5d15be0c16fd583466d653660c2d83707454dee76
|
| 3 |
+
size 160486456
|
e45/S1-E45-SHR-ts1-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 |
+
},
|
| 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 |
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"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 |
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"out_proj",
|
| 46 |
+
"q_proj",
|
| 47 |
+
"up_proj",
|
| 48 |
+
"v_proj"
|
| 49 |
+
],
|
| 50 |
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"target_parameters": null,
|
| 51 |
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"task_type": null,
|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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}
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter_vllm/adapter_model.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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| 2 |
+
oid sha256:c86cb63a52fa53ecfb0dd2c468d9705ae70fac6fde6aa6cd9aae2e4e2843bfd7
|
| 3 |
+
size 176641832
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/adapter_vllm/decision_head.json
ADDED
|
@@ -0,0 +1,99 @@
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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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|
| 29 |
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|
| 30 |
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|
| 31 |
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| 32 |
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| 34 |
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| 35 |
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| 39 |
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|
| 40 |
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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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| 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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| 85 |
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|
| 86 |
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"H",
|
| 87 |
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| 88 |
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"J",
|
| 89 |
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"K",
|
| 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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"template_version": "bare-v1"
|
| 97 |
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},
|
| 98 |
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"note": "decision logits = lm_head-LoRA logprobs of verbalizer ids + bias, then per-kind temperature"
|
| 99 |
+
}
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/calibration.json
ADDED
|
@@ -0,0 +1,29 @@
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|
| 1 |
+
{
|
| 2 |
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"version": 1,
|
| 3 |
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"per_kind": {
|
| 4 |
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|
| 5 |
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|
| 6 |
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"score": 0.9920105000320746
|
| 7 |
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},
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| 8 |
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| 9 |
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|
| 10 |
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"n": 1087,
|
| 11 |
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"T": 0.9782350344526988,
|
| 12 |
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|
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|
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| 15 |
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"choice": {
|
| 16 |
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|
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|
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| 25 |
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| 26 |
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}
|
| 27 |
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},
|
| 28 |
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"source": "models/e45/S1-E45-SHR-ts1-syn/ckpt-16000"
|
| 29 |
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}
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/head.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:4bf243817030ce0054d6b9aa79b60f6d9ec60ea67c200f5bc8fe5e4f0cb58fd3
|
| 3 |
+
size 393464
|
e45/S1-E45-SHR-ts1-syn/ckpt-16000/judge_config.json
ADDED
|
@@ -0,0 +1,164 @@
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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| 5 |
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|
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| 7 |
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| 10 |
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|
| 11 |
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| 12 |
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| 13 |
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|
| 14 |
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| 15 |
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"choice": [
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| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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},
|
| 20 |
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"verbalizers": [
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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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"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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| 55 |
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| 58 |
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| 60 |
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| 61 |
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| 62 |
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| 63 |
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|
| 64 |
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| 68 |
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|
| 69 |
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| 70 |
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| 71 |
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46,
|
| 72 |
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| 73 |
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],
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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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"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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| 85 |
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|
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|
| 89 |
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|
| 90 |
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| 91 |
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| 92 |
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| 93 |
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| 96 |
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| 97 |
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|
| 100 |
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},
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| 101 |
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"trained_stage": "e16",
|
| 102 |
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"source_checkpoint": "models/e45/S1-E45-SHR-ts1-syn/ckpt-16000",
|
| 103 |
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"softcap": null,
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| 104 |
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"e16": {
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| 105 |
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"data": "data/e45/E45-SHR",
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| 106 |
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"name": null,
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"init": "released",
|
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"objective": "s-log",
|
| 114 |
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| 118 |
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| 130 |
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|
| 163 |
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|
| 164 |
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|
e45/S1-E45-SHR-ts1-syn/train_log.jsonl
ADDED
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@@ -0,0 +1,57 @@
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|
| 1 |
+
{"time": "18:53:33", "event": "start", "data": "data/e45/E45-SHR", "data_manifest": {"arm": "E45-SHR", "name": null, "train_sha256": "cfe452b00b8ac702c42580427823a8e4bf112271713c1fea190e1f3214bb6fbf", "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": 1, "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": 130.59742903709412}
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| 51 |
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{"time": "21:50:21", "event": "step", "step": 460, "rows_seen": 14720, "lr": 6.585509610150972e-06, "tok_per_s": 789.6758922735186, "loss": 0.5831257402896881, "entropy": 0.5738185830414295, "sharp": 0.19984791800379753}
|
| 52 |
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{"time": "21:54:10", "event": "step", "step": 470, "rows_seen": 15040, "lr": 5.894036597333646e-06, "tok_per_s": 790.0808091776232, "loss": 0.6089097522199154, "entropy": 0.5740026235580444, "sharp": 0.20401583053171635}
|
| 53 |
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{"time": "21:57:52", "event": "step", "step": 480, "rows_seen": 15360, "lr": 5.398045191744809e-06, "tok_per_s": 790.6181575917767, "loss": 0.5815652180463076, "entropy": 0.585292112082243, "sharp": 0.19261294417083263}
|
| 54 |
+
{"time": "22:01:41", "event": "step", "step": 490, "rows_seen": 15680, "lr": 5.099615753708697e-06, "tok_per_s": 791.1440328337729, "loss": 0.5746835768222809, "entropy": 0.6032003685832024, "sharp": 0.1721150204539299}
|
| 55 |
+
{"time": "22:05:23", "event": "step", "step": 500, "rows_seen": 16000, "lr": 5e-06, "tok_per_s": 791.7637853489691, "loss": 0.5333664081990719, "entropy": 0.5551153346896172, "sharp": 0.20426847971975803}
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| 56 |
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{"time": "22:06:53", "event": "val", "step": 500, "rows_seen": 16000, "n": 500, "dropped_long": 0, "noul_ce": 0.5648979544639587, "noul_T": 1.0084058584423725, "noul_auc": 0.7487637339454187, "noul_acc": 0.708, "noul_f1": 0.7760736196319018, "noul_nll": 0.5700209506750107, "noul_ece": 0.05854451191425324, "noul_brier": 0.19479488186794344, "noul_sharp": 0.2042987048625946, "entropy": 0.5634372234344482}
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| 57 |
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{"time": "22:10:06", "event": "ckpt", "tag": "ckpt-16000", "rows_seen": 16000, "replay_seen": 842, "step": 500, "tokens": 9113125, "tok_per_s": 772.8512325148486, "rows_per_s": 1.4283092192638802, "val": {"n": 1200, "dropped_long": 0, "noul_ce": 0.5506337285041809, "noul_T": 0.9782350344526988, "choice_ce": 0.6639683246612549, "choice_T": 1.0346329807161856, "score_ce": 1.0500822067260742, "score_T": 0.9920105000320746, "noul_auc": 0.7479509333333333, "noul_acc": 0.708, "noul_f1": 0.7830609212481426, "noul_nll": 0.5656526157269254, "noul_ece": 0.03333447651565077, "noul_brier": 0.19313562662046876, "noul_sharp": 0.20571254193782806, "entropy": 0.5634832382202148}, "dropped_long": 0, "peak_gib": 18.23796796798706}
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