gpt2_m090_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: 1.1994
- Accuracy: 0.6811
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 |
---|---|---|---|---|
2.8751 | 0.0519 | 1000 | 2.4323 | 0.4504 |
1.9622 | 0.1037 | 2000 | 1.7853 | 0.5717 |
1.7125 | 0.1556 | 3000 | 1.6003 | 0.6046 |
1.5958 | 0.2074 | 4000 | 1.5009 | 0.6225 |
1.5199 | 0.2593 | 5000 | 1.4369 | 0.6347 |
1.4675 | 0.3112 | 6000 | 1.3928 | 0.6430 |
1.4297 | 0.3630 | 7000 | 1.3593 | 0.6495 |
1.3993 | 0.4149 | 8000 | 1.3303 | 0.6549 |
1.373 | 0.4668 | 9000 | 1.3077 | 0.6593 |
1.3537 | 0.5186 | 10000 | 1.2885 | 0.6631 |
1.3332 | 0.5705 | 11000 | 1.2709 | 0.6667 |
1.3207 | 0.6223 | 12000 | 1.2552 | 0.6697 |
1.3064 | 0.6742 | 13000 | 1.2452 | 0.6718 |
1.2972 | 0.7261 | 14000 | 1.2339 | 0.6740 |
1.2823 | 0.7779 | 15000 | 1.2240 | 0.6759 |
1.2703 | 0.8298 | 16000 | 1.2162 | 0.6775 |
1.2674 | 0.8817 | 17000 | 1.2090 | 0.6791 |
1.2591 | 0.9335 | 18000 | 1.2037 | 0.6802 |
1.2579 | 0.9854 | 19000 | 1.1997 | 0.6811 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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