babylm-base2.5m-gpt2
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3906
- Accuracy: 0.4129
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 195
- training_steps: 19500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.8389 | 0.1065 | 200 | 4.8806 | 0.3144 |
| 4.8812 | 0.2130 | 400 | 4.4667 | 0.3240 |
| 4.707 | 0.3195 | 600 | 4.2884 | 0.3341 |
| 4.479 | 0.4260 | 800 | 4.2022 | 0.3348 |
| 4.2839 | 0.5325 | 1000 | 4.1496 | 0.3363 |
| 4.1679 | 0.6390 | 1200 | 4.1096 | 0.3369 |
| 4.125 | 0.7455 | 1400 | 4.0623 | 0.3393 |
| 3.9613 | 0.8520 | 1600 | 4.0172 | 0.3394 |
| 3.9268 | 0.9585 | 1800 | 4.0097 | 0.3367 |
| 3.8225 | 1.0650 | 2000 | 3.9714 | 0.3417 |
| 2.6933 | 2.1299 | 4000 | 3.6543 | 0.3824 |
| 2.3328 | 3.1949 | 6000 | 3.5196 | 0.3985 |
| 2.1778 | 4.2599 | 8000 | 3.4668 | 0.4016 |
| 2.0886 | 5.3248 | 10000 | 3.4159 | 0.4073 |
| 1.9842 | 6.3898 | 12000 | 3.3836 | 0.4104 |
| 1.9168 | 7.4547 | 14000 | 3.3775 | 0.4112 |
| 1.8811 | 8.5197 | 16000 | 3.3978 | 0.4121 |
| 1.8392 | 9.5847 | 18000 | 3.3874 | 0.4125 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4
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