de_childes_42
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1897
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40000
- training_steps: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.5021 | 2000 | 7.0336 |
| 6.9417 | 3.0041 | 4000 | 5.8112 |
| 6.9417 | 4.5062 | 6000 | 5.4586 |
| 5.2077 | 6.0083 | 8000 | 5.1717 |
| 5.2077 | 7.5103 | 10000 | 4.9583 |
| 4.7315 | 9.0124 | 12000 | 4.8002 |
| 4.7315 | 10.5145 | 14000 | 4.6706 |
| 4.4253 | 12.0165 | 16000 | 4.5552 |
| 4.4253 | 13.5186 | 18000 | 4.4522 |
| 4.1962 | 15.0207 | 20000 | 4.3739 |
| 4.1962 | 16.5227 | 22000 | 4.2925 |
| 4.0105 | 18.0248 | 24000 | 4.2277 |
| 4.0105 | 19.5268 | 26000 | 4.1706 |
| 3.857 | 21.0289 | 28000 | 4.1245 |
| 3.857 | 22.5310 | 30000 | 4.0846 |
| 3.7298 | 24.0330 | 32000 | 4.0589 |
| 3.7298 | 25.5351 | 34000 | 4.0266 |
| 3.6218 | 27.0372 | 36000 | 4.0028 |
| 3.6218 | 28.5392 | 38000 | 3.9863 |
| 3.5278 | 30.0413 | 40000 | 3.9732 |
| 3.5278 | 31.5434 | 42000 | 3.9720 |
| 3.4351 | 33.0454 | 44000 | 3.9599 |
| 3.4351 | 34.5475 | 46000 | 3.9566 |
| 3.3444 | 36.0496 | 48000 | 3.9572 |
| 3.3444 | 37.5516 | 50000 | 3.9680 |
| 3.2651 | 39.0537 | 52000 | 3.9788 |
| 3.2651 | 40.5558 | 54000 | 3.9815 |
| 3.1966 | 42.0578 | 56000 | 3.9928 |
| 3.1966 | 43.5599 | 58000 | 4.0061 |
| 3.1344 | 45.0620 | 60000 | 4.0126 |
| 3.1344 | 46.5640 | 62000 | 4.0198 |
| 3.0785 | 48.0661 | 64000 | 4.0377 |
| 3.0785 | 49.5682 | 66000 | 4.0502 |
| 3.0287 | 51.0702 | 68000 | 4.0644 |
| 3.0287 | 52.5723 | 70000 | 4.0714 |
| 2.9837 | 54.0744 | 72000 | 4.0852 |
| 2.9837 | 55.5764 | 74000 | 4.0964 |
| 2.9422 | 57.0785 | 76000 | 4.1148 |
| 2.9422 | 58.5805 | 78000 | 4.1221 |
| 2.9052 | 60.0826 | 80000 | 4.1276 |
| 2.9052 | 61.5847 | 82000 | 4.1346 |
| 2.8708 | 63.0867 | 84000 | 4.1505 |
| 2.8708 | 64.5888 | 86000 | 4.1574 |
| 2.839 | 66.0909 | 88000 | 4.1675 |
| 2.839 | 67.5929 | 90000 | 4.1727 |
| 2.8117 | 69.0950 | 92000 | 4.1767 |
| 2.8117 | 70.5971 | 94000 | 4.1823 |
| 2.7886 | 72.0991 | 96000 | 4.1867 |
| 2.7886 | 73.6012 | 98000 | 4.1872 |
| 2.768 | 75.1033 | 100000 | 4.1897 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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