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bert_large_yc_recipe_30
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 121 | 0.0026 |
| No log | 2.0 | 242 | 0.0006 |
| No log | 3.0 | 363 | 0.0001 |
| No log | 4.0 | 484 | 0.0000 |
| 0.057 | 5.0 | 605 | 0.0000 |
| 0.057 | 6.0 | 726 | 0.0000 |
| 0.057 | 7.0 | 847 | 0.0000 |
| 0.057 | 8.0 | 968 | 0.0000 |
| 0.0002 | 9.0 | 1089 | 0.0001 |
| 0.0002 | 10.0 | 1210 | 0.0001 |
| 0.0002 | 11.0 | 1331 | 0.0002 |
| 0.0002 | 12.0 | 1452 | 0.0001 |
| 0.0002 | 13.0 | 1573 | 0.0001 |
| 0.0002 | 14.0 | 1694 | 0.0001 |
| 0.0002 | 15.0 | 1815 | 0.0001 |
| 0.0002 | 16.0 | 1936 | 0.0001 |
| 0.0 | 17.0 | 2057 | 0.0001 |
| 0.0 | 18.0 | 2178 | 0.0001 |
| 0.0 | 19.0 | 2299 | 0.0001 |
| 0.0 | 20.0 | 2420 | 0.0001 |
| 0.0 | 21.0 | 2541 | 0.0001 |
| 0.0 | 22.0 | 2662 | 0.0001 |
| 0.0 | 23.0 | 2783 | 0.0001 |
| 0.0 | 24.0 | 2904 | 0.0001 |
| 0.0 | 25.0 | 3025 | 0.0000 |
| 0.0 | 26.0 | 3146 | 0.0000 |
| 0.0 | 27.0 | 3267 | 0.0000 |
| 0.0 | 28.0 | 3388 | 0.0000 |
| 0.0 | 29.0 | 3509 | 0.0000 |
| 0.0 | 30.0 | 3630 | 0.0000 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.11.0a0+17540c5
- Datasets 2.4.0
- Tokenizers 0.12.1
