gpt2_m000_tiny-stories_1024
This model is a fine-tuned version of on the roneneldan/TinyStories dataset. It achieves the following results on the evaluation set:
- Loss: 1.2184
- Accuracy: 0.6771
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 |
|---|---|---|---|---|
| 2.9359 | 0.0524 | 1000 | 2.4815 | 0.4410 |
| 1.9921 | 0.1048 | 2000 | 1.8065 | 0.5669 |
| 1.7408 | 0.1572 | 3000 | 1.6246 | 0.5992 |
| 1.6193 | 0.2095 | 4000 | 1.5241 | 0.6175 |
| 1.5447 | 0.2619 | 5000 | 1.4585 | 0.6298 |
| 1.4956 | 0.3143 | 6000 | 1.4138 | 0.6385 |
| 1.4512 | 0.3667 | 7000 | 1.3794 | 0.6447 |
| 1.4238 | 0.4191 | 8000 | 1.3509 | 0.6502 |
| 1.3962 | 0.4715 | 9000 | 1.3292 | 0.6546 |
| 1.3753 | 0.5238 | 10000 | 1.3088 | 0.6583 |
| 1.3563 | 0.5762 | 11000 | 1.2903 | 0.6623 |
| 1.3393 | 0.6286 | 12000 | 1.2765 | 0.6650 |
| 1.328 | 0.6810 | 13000 | 1.2634 | 0.6677 |
| 1.3111 | 0.7334 | 14000 | 1.2529 | 0.6699 |
| 1.3047 | 0.7858 | 15000 | 1.2427 | 0.6721 |
| 1.2919 | 0.8381 | 16000 | 1.2342 | 0.6736 |
| 1.2863 | 0.8905 | 17000 | 1.2267 | 0.6753 |
| 1.2819 | 0.9429 | 18000 | 1.2216 | 0.6764 |
| 1.2759 | 0.9953 | 19000 | 1.2184 | 0.6771 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Dataset used to train jonasknobloch/gpt2_m000_tiny-stories_1024
Evaluation results
- Accuracy on roneneldan/TinyStoriesself-reported0.677