gpt2_m100_tiny-stories_1024_dpos
This model is a fine-tuned version of on the roneneldan/TinyStories dataset. It achieves the following results on the evaluation set:
- Loss: 1.1579
- Accuracy: 0.6901
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 |
---|---|---|---|---|
2.801 | 0.0506 | 1000 | 2.3554 | 0.4658 |
1.8977 | 0.1012 | 2000 | 1.7248 | 0.5834 |
1.658 | 0.1518 | 3000 | 1.5498 | 0.6145 |
1.5426 | 0.2024 | 4000 | 1.4542 | 0.6321 |
1.4721 | 0.2530 | 5000 | 1.3930 | 0.6435 |
1.4237 | 0.3036 | 6000 | 1.3497 | 0.6517 |
1.387 | 0.3543 | 7000 | 1.3162 | 0.6580 |
1.3537 | 0.4049 | 8000 | 1.2899 | 0.6633 |
1.3306 | 0.4555 | 9000 | 1.2683 | 0.6676 |
1.3127 | 0.5061 | 10000 | 1.2474 | 0.6716 |
1.2925 | 0.5567 | 11000 | 1.2326 | 0.6745 |
1.2779 | 0.6073 | 12000 | 1.2171 | 0.6778 |
1.262 | 0.6579 | 13000 | 1.2051 | 0.6802 |
1.2502 | 0.7085 | 14000 | 1.1949 | 0.6823 |
1.2413 | 0.7591 | 15000 | 1.1852 | 0.6843 |
1.2354 | 0.8097 | 16000 | 1.1773 | 0.6857 |
1.2254 | 0.8603 | 17000 | 1.1699 | 0.6874 |
1.2186 | 0.9109 | 18000 | 1.1639 | 0.6887 |
1.2155 | 0.9615 | 19000 | 1.1597 | 0.6897 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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