bert-crossencoder-kl_divergence
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9919
- Accuracy: 0.6084
- Precision: 0.6124
- Recall: 0.6084
- F1: 0.6099
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.282 | 1.0 | 78 | 1.2172 | 0.4951 | 0.3948 | 0.4951 | 0.4061 |
| 1.0377 | 2.0 | 156 | 1.0246 | 0.5793 | 0.6114 | 0.5793 | 0.5550 |
| 0.9037 | 3.0 | 234 | 0.9440 | 0.6084 | 0.6178 | 0.6084 | 0.6015 |
| 0.7861 | 4.0 | 312 | 0.9381 | 0.6343 | 0.6425 | 0.6343 | 0.6356 |
| 0.5607 | 5.0 | 390 | 0.9718 | 0.6052 | 0.6114 | 0.6052 | 0.6034 |
| 0.4532 | 6.0 | 468 | 0.9680 | 0.6278 | 0.6290 | 0.6278 | 0.6275 |
| 0.3763 | 7.0 | 546 | 0.9919 | 0.6084 | 0.6124 | 0.6084 | 0.6099 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0