pythia_14m_sft
This model is a fine-tuned version of EleutherAI/pythia-14m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0709
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.5962 | 0.0889 | 100 | 3.4716 |
3.4759 | 0.1778 | 200 | 3.4017 |
3.4434 | 0.2667 | 300 | 3.3713 |
3.3847 | 0.3556 | 400 | 3.3427 |
3.359 | 0.4444 | 500 | 3.3186 |
3.3447 | 0.5333 | 600 | 3.2899 |
3.3099 | 0.6222 | 700 | 3.2654 |
3.2775 | 0.7111 | 800 | 3.2482 |
3.2512 | 0.8 | 900 | 3.2254 |
3.2302 | 0.8889 | 1000 | 3.2151 |
3.1752 | 0.9778 | 1100 | 3.1929 |
3.1005 | 1.0667 | 1200 | 3.1916 |
3.0798 | 1.1556 | 1300 | 3.1778 |
3.073 | 1.2444 | 1400 | 3.1688 |
3.1032 | 1.3333 | 1500 | 3.1707 |
3.0417 | 1.4222 | 1600 | 3.1607 |
3.075 | 1.5111 | 1700 | 3.1573 |
3.0675 | 1.6 | 1800 | 3.1476 |
3.0719 | 1.6889 | 1900 | 3.1424 |
3.0469 | 1.7778 | 2000 | 3.1344 |
3.0643 | 1.8667 | 2100 | 3.1257 |
3.0375 | 1.9556 | 2200 | 3.1195 |
2.9736 | 2.0444 | 2300 | 3.1130 |
2.9915 | 2.1333 | 2400 | 3.1146 |
2.9285 | 2.2222 | 2500 | 3.1061 |
2.9535 | 2.3111 | 2600 | 3.0981 |
2.9691 | 2.4 | 2700 | 3.0966 |
2.9079 | 2.4889 | 2800 | 3.0889 |
2.9216 | 2.5778 | 2900 | 3.0847 |
2.924 | 2.6667 | 3000 | 3.0795 |
2.9529 | 2.7556 | 3100 | 3.0775 |
2.9375 | 2.8444 | 3200 | 3.0732 |
2.8904 | 2.9333 | 3300 | 3.0709 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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