End of training

README.md

@@ -1,7 +1,9 @@
 ---
-library_name: transformers
-license: mit
 base_model: gpt2
+datasets:
+- wikimedia/wikipedia
+library_name: Distily
+license: mit
 tags:
 - bitnet
 - 1.58b
@@ -11,75 +13,147 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
-# distily_multi_experiment
+# Summary
 
-This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 11.8595
+Distilled with [Distily](https://github.com/lapp0/distily) library
+using teacher model [gpt2](https://huggingface.co/gpt2)
+on dataset [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia).
 
-## Model description
-
-More information needed
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment.
 
-## Intended uses & limitations
+# Model description
 
 More information needed
 
-## Training and evaluation data
+# Intended uses & limitations
 
 More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
+-->
+
+# Model Architecture:
+- **Architecture**: `GPT2LMHeadModel`
+- **Total Parameters**: 124,439,808
+- **Data Type (dtype)**: torch.bfloat16
+- **Model Size**: 0.24 GB
+
+
+# Evaluation Metrics Comparison
+
+| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
+| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
+| **teacher eval** |  | 43.25 | 61.25 |  |  |  |  | 11.6875 | 19.125 |
+| 0 | 0 | 1133871366144.0 | 97306779058176.0 | 44.6892 | 25.2062 | 99.182 | 12.418 | 2785017856.0 | 54425825574912.0 |
+| 2500 | 0.0404 | 1648.0 | 17664.0 | 20.4150 | 25.2355 | 99.067 | 12.403 | 1368.0 | 30464.0 |
+| 5000 | 0.0808 | 498.0 | 3152.0 | 18.2270 | 25.2737 | 98.917 | 12.384 | 338.0 | 620.0 |
+| 7500 | 0.1212 | 272.0 | 1288.0 | 16.8848 | 25.2363 | 99.064 | 12.403 | 241.0 | 262.0 |
+| 10000 | 0.1616 | 199.0 | 852.0 | 16.0482 | 25.2552 | 98.99 | 12.394 | 181.0 | 160.0 |
+| 12500 | 0.2020 | 142.0 | 544.0 | 14.9888 | 25.2627 | 98.96 | 12.39 | 122.0 | 159.0 |
+| 15000 | 0.2424 | 119.0 | 506.0 | 14.4049 | 25.2537 | 98.995 | 12.394 | 95.5 | 151.0 |
+| 17500 | 0.2828 | 98.0 | 376.0 | 14.0632 | 25.1898 | 99.247 | 12.426 | 74.0 | 128.0 |
+| 20000 | 0.3232 | 76.5 | 280.0 | 13.5213 | 25.2312 | 99.084 | 12.405 | 68.0 | 94.0 |
+| 22500 | 0.3636 | 66.0 | 210.0 | 13.0349 | 25.2005 | 99.204 | 12.42 | 49.25 | 73.5 |
+| 25000 | 0.4040 | 62.25 | 187.0 | 12.8246 | 25.2755 | 98.91 | 12.384 | 44.75 | 65.5 |
+| 27500 | 0.4444 | 60.25 | 175.0 | 12.7070 | 25.2654 | 98.949 | 12.388 | 43.25 | 72.5 |
+| 30000 | 0.4848 | 62.25 | 183.0 | 12.7168 | 25.2653 | 98.95 | 12.389 | 42.25 | 87.0 |
+| 32500 | 0.5253 | 59.0 | 184.0 | 12.6674 | 25.2119 | 99.16 | 12.415 | 37.75 | 70.5 |
+| 35000 | 0.5657 | 58.0 | 176.0 | 12.5288 | 25.2238 | 99.113 | 12.409 | 34.75 | 50.0 |
+| 37500 | 0.6061 | 56.5 | 166.0 | 12.4810 | 25.192 | 99.238 | 12.425 | 36.75 | 69.5 |
+| 40000 | 0.6465 | 55.0 | 151.0 | 12.4422 | 25.2105 | 99.165 | 12.415 | 34.0 | 48.25 |
+| 42500 | 0.6869 | 52.75 | 161.0 | 12.3894 | 25.258 | 98.979 | 12.392 | 33.5 | 58.75 |
+| 45000 | 0.7273 | 51.25 | 134.0 | 12.1660 | 25.1916 | 99.239 | 12.425 | 29.75 | 43.0 |
+| 47500 | 0.7677 | 48.75 | 129.0 | 12.125 | 25.243 | 99.037 | 12.399 | 28.625 | 38.25 |
+| 50000 | 0.8081 | 49.75 | 126.5 | 12.0924 | 25.25 | 99.01 | 12.396 | 28.375 | 35.0 |
+| 52500 | 0.8485 | 50.75 | 125.0 | 12.0760 | 25.2184 | 99.134 | 12.412 | 28.0 | 39.0 |
+| 55000 | 0.8889 | 49.75 | 124.5 | 12.0411 | 25.2538 | 98.995 | 12.394 | 27.625 | 36.75 |
+| 57500 | 0.9293 | 49.0 | 120.5 | 12.0289 | 25.2405 | 99.047 | 12.401 | 27.375 | 34.5 |
+| 60000 | 0.9697 | 48.75 | 120.5 | 12.0196 | 25.192 | 99.238 | 12.425 | 27.375 | 35.0 |
+| 61875 | 1.0 | 49.0 | 121.0 | 12.0190 | 25.1853 | 99.264 | 12.428 | 27.375 | 35.0 |
+
+# Resource Usage Comparison
+
+- VRAM Use: 7.7823 GB
+
+# Distillation (Teacher -> Student) Architecture Difference:
+
+- **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
+- **Total Parameters**: 124,439,808 -> 124,439,808
+- **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
+- **Model Size**: 0.24 GB -> 0.24 GB
+
+<details>
+<summary>Module Diff Details</summary>
+
+```diff
+
+```
+
+</details>
+<br/>
+
+# Train Dataset
+Trained on 145,731,804 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
+
+- Num Samples: `247,500`
+- Subset: `20231101.en`
+- Split: `train`
+
+
+# Training Objective
+
+```
+DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=25.0, loss_fn=cos, layer_mapper=layer-2))
+```
+
+# Hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 4
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.5
-- num_epochs: 1.0
-
-### Training results
-
-| Training Loss | Epoch  | Step  | Validation Loss |
-|:-------------:|:------:|:-----:|:---------------:|
-| No log        | 0      | 0     | 45.5392         |
-| 19.25         | 0.0404 | 2500  | 20.5160         |
-| 17.0          | 0.0808 | 5000  | 18.1646         |
-| 16.375        | 0.1212 | 7500  | 16.8100         |
-| 18.5          | 0.1616 | 10000 | 15.9662         |
-| 18.125        | 0.2020 | 12500 | 14.8913         |
-| 16.125        | 0.2424 | 15000 | 14.2909         |
-| 13.875        | 0.2828 | 17500 | 13.9054         |
-| 12.5625       | 0.3232 | 20000 | 13.4260         |
-| 13.8125       | 0.3636 | 22500 | 12.9026         |
-| 14.5625       | 0.4040 | 25000 | 12.6783         |
-| 15.1875       | 0.4444 | 27500 | 12.5651         |
-| 13.4375       | 0.4848 | 30000 | 12.5742         |
-| 6.8125        | 0.5253 | 32500 | 12.5106         |
-| 12.0          | 0.5657 | 35000 | 12.3849         |
-| 13.9375       | 0.6061 | 37500 | 12.3297         |
-| 5.375         | 0.6465 | 40000 | 12.2764         |
-| 20.625        | 0.6869 | 42500 | 12.2612         |
-| 10.0          | 0.7273 | 45000 | 12.0058         |
-| 18.75         | 0.7677 | 47500 | 11.9614         |
-| 10.0625       | 0.8081 | 50000 | 11.9339         |
-| 16.0          | 0.8485 | 52500 | 11.9123         |
-| 18.625        | 0.8889 | 55000 | 11.8770         |
-| 15.875        | 0.9293 | 57500 | 11.8680         |
-| 11.25         | 0.9697 | 60000 | 11.8611         |
-
-
-### Framework versions
 
+<details>
+<summary>Expand</summary>
+
+- learning_rate: `0.0001`
+- train_batch_size: `4`
+- eval_batch_size: `8`
+- seed: `42`
+- optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
+- lr_scheduler_type: `linear`
+- lr_scheduler_warmup_ratio: `0.5`
+- num_epochs: `1.0`
+- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=25.0, loss_fn=cos, layer_mapper=layer-2))`
+- train_embeddings: `True`
+- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f040856c4f0>`
+- student_model_name_or_path: `None`
+- student_config_name_or_path: `None`
+- student_model_config: `None`
+- reinitialize_weights: `None`
+- copy_teacher_modules: `[('lm_head', False)]`
+- student_model_as_bitnet: `True`
+- student_model_compile: `False`
+- dropout: `None`
+- teacher_model_name_or_path: `gpt2`
+- teacher_load_in_8bit: `False`
+- teacher_load_in_4bit: `False`
+- teacher_model_compile: `False`
+- dataset_uri: `wikimedia/wikipedia`
+- dataset_subset: `20231101.en`
+- dataset_split: `train`
+- dataset_column_name: `text`
+- dataset_sample_size: `250000`
+- dataset_test_size: `0.01`
+- gradient_accumulation_steps: `1`
+- weight_decay: `0.0`
+- max_grad_norm: `1.0`
+- warmup_ratio: `0.5`
+- warmup_steps: `0`
+- gradient_checkpointing: `True`
+
+</details>
+<br/>
+
+
+# Framework Versions
+- Distily 0.2.0
 - Transformers 4.44.1
 - Pytorch 2.5.0.dev20240821+cu121
 - Datasets 2.21.0
-- Tokenizers 0.19.1

logs/attn_loss_fn=cos, attn_weight=25.0, layer_mapper=layer-2, projector=linear/events.out.tfevents.1724403552.e3f806ea38c9

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