| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - roneneldan/TinyStories |
| metrics: |
| - accuracy |
| model-index: |
| - name: gpt2_m030_tiny-stories_1024 |
| results: |
| - task: |
| name: Causal Language Modeling |
| type: text-generation |
| dataset: |
| name: roneneldan/TinyStories |
| type: roneneldan/TinyStories |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.6756425005551174 |
| --- |
| |
| <!-- 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. --> |
|
|
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/scads-nlp/morph-gpt_gpt2_tiny-stories/runs/t3jfpuq6) |
| # gpt2_m030_tiny-stories_1024 |
| |
| This model is a fine-tuned version of [](https://huggingface.co/) on the roneneldan/TinyStories dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2217 |
| - Accuracy: 0.6756 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1.0 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:-----:|:---------------:|:--------:| |
| | 2.9308 | 0.0525 | 1000 | 2.4752 | 0.4408 | |
| | 1.9919 | 0.1050 | 2000 | 1.8136 | 0.5648 | |
| | 1.7406 | 0.1575 | 3000 | 1.6235 | 0.5984 | |
| | 1.6185 | 0.2101 | 4000 | 1.5258 | 0.6165 | |
| | 1.5461 | 0.2626 | 5000 | 1.4625 | 0.6282 | |
| | 1.4955 | 0.3151 | 6000 | 1.4170 | 0.6368 | |
| | 1.4553 | 0.3676 | 7000 | 1.3824 | 0.6433 | |
| | 1.4218 | 0.4201 | 8000 | 1.3532 | 0.6492 | |
| | 1.3986 | 0.4726 | 9000 | 1.3305 | 0.6537 | |
| | 1.3722 | 0.5252 | 10000 | 1.3100 | 0.6575 | |
| | 1.3573 | 0.5777 | 11000 | 1.2934 | 0.6608 | |
| | 1.3448 | 0.6302 | 12000 | 1.2785 | 0.6639 | |
| | 1.3291 | 0.6827 | 13000 | 1.2657 | 0.6665 | |
| | 1.3174 | 0.7352 | 14000 | 1.2551 | 0.6686 | |
| | 1.3052 | 0.7877 | 15000 | 1.2463 | 0.6704 | |
| | 1.2968 | 0.8402 | 16000 | 1.2366 | 0.6725 | |
| | 1.2856 | 0.8928 | 17000 | 1.2308 | 0.6735 | |
| | 1.2817 | 0.9453 | 18000 | 1.2249 | 0.6749 | |
| | 1.2814 | 0.9978 | 19000 | 1.2216 | 0.6757 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.2.2+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
