de_childes_13
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1847
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: 13
- 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 | 7.0542 |
| 6.9608 | 3.0041 | 4000 | 5.8207 |
| 6.9608 | 4.5062 | 6000 | 5.4596 |
| 5.2094 | 6.0083 | 8000 | 5.1686 |
| 5.2094 | 7.5103 | 10000 | 4.9647 |
| 4.7331 | 9.0124 | 12000 | 4.8010 |
| 4.7331 | 10.5145 | 14000 | 4.6684 |
| 4.425 | 12.0165 | 16000 | 4.5528 |
| 4.425 | 13.5186 | 18000 | 4.4599 |
| 4.1941 | 15.0207 | 20000 | 4.3706 |
| 4.1941 | 16.5227 | 22000 | 4.2942 |
| 4.0094 | 18.0248 | 24000 | 4.2263 |
| 4.0094 | 19.5268 | 26000 | 4.1749 |
| 3.8583 | 21.0289 | 28000 | 4.1299 |
| 3.8583 | 22.5310 | 30000 | 4.0866 |
| 3.7325 | 24.0330 | 32000 | 4.0591 |
| 3.7325 | 25.5351 | 34000 | 4.0317 |
| 3.6244 | 27.0372 | 36000 | 4.0061 |
| 3.6244 | 28.5392 | 38000 | 3.9925 |
| 3.5304 | 30.0413 | 40000 | 3.9792 |
| 3.5304 | 31.5434 | 42000 | 3.9642 |
| 3.4371 | 33.0454 | 44000 | 3.9606 |
| 3.4371 | 34.5475 | 46000 | 3.9557 |
| 3.3462 | 36.0496 | 48000 | 3.9565 |
| 3.3462 | 37.5516 | 50000 | 3.9676 |
| 3.2678 | 39.0537 | 52000 | 3.9713 |
| 3.2678 | 40.5558 | 54000 | 3.9783 |
| 3.1984 | 42.0578 | 56000 | 3.9919 |
| 3.1984 | 43.5599 | 58000 | 3.9993 |
| 3.1371 | 45.0620 | 60000 | 4.0153 |
| 3.1371 | 46.5640 | 62000 | 4.0182 |
| 3.0817 | 48.0661 | 64000 | 4.0311 |
| 3.0817 | 49.5682 | 66000 | 4.0445 |
| 3.0311 | 51.0702 | 68000 | 4.0579 |
| 3.0311 | 52.5723 | 70000 | 4.0714 |
| 2.9858 | 54.0744 | 72000 | 4.0819 |
| 2.9858 | 55.5764 | 74000 | 4.0889 |
| 2.9448 | 57.0785 | 76000 | 4.1067 |
| 2.9448 | 58.5805 | 78000 | 4.1096 |
| 2.9072 | 60.0826 | 80000 | 4.1248 |
| 2.9072 | 61.5847 | 82000 | 4.1356 |
| 2.8728 | 63.0867 | 84000 | 4.1422 |
| 2.8728 | 64.5888 | 86000 | 4.1524 |
| 2.8421 | 66.0909 | 88000 | 4.1611 |
| 2.8421 | 67.5929 | 90000 | 4.1661 |
| 2.8146 | 69.0950 | 92000 | 4.1721 |
| 2.8146 | 70.5971 | 94000 | 4.1775 |
| 2.7902 | 72.0991 | 96000 | 4.1821 |
| 2.7902 | 73.6012 | 98000 | 4.1832 |
| 2.7708 | 75.1033 | 100000 | 4.1847 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1