bert-large-cased-sigir-support-no-label-20
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2135
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: 4e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7629 | 1.0 | 246 | 2.2876 |
| 2.2004 | 2.0 | 492 | 1.9698 |
| 1.9011 | 3.0 | 738 | 1.8034 |
| 1.7521 | 4.0 | 984 | 1.7313 |
| 1.6405 | 5.0 | 1230 | 1.6195 |
| 1.553 | 6.0 | 1476 | 1.5437 |
| 1.4707 | 7.0 | 1722 | 1.5072 |
| 1.398 | 8.0 | 1968 | 1.4477 |
| 1.3563 | 9.0 | 2214 | 1.4426 |
| 1.3085 | 10.0 | 2460 | 1.4250 |
| 1.2678 | 11.0 | 2706 | 1.3580 |
| 1.2255 | 12.0 | 2952 | 1.3553 |
| 1.1901 | 13.0 | 3198 | 1.3094 |
| 1.1656 | 14.0 | 3444 | 1.2731 |
| 1.1371 | 15.0 | 3690 | 1.3012 |
| 1.1131 | 16.0 | 3936 | 1.2850 |
| 1.0945 | 17.0 | 4182 | 1.2473 |
| 1.0774 | 18.0 | 4428 | 1.2770 |
| 1.0531 | 19.0 | 4674 | 1.2285 |
| 1.0608 | 20.0 | 4920 | 1.2645 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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