bert_base_train_book_ent_2_inv_qnli
This model is a fine-tuned version of gokulsrinivasagan/bert_base_train_book_ent_2_inv on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6479
- Accuracy: 0.6156
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6711 | 1.0 | 410 | 0.6479 | 0.6156 |
| 0.6373 | 2.0 | 820 | 0.6502 | 0.6240 |
| 0.5837 | 3.0 | 1230 | 0.6906 | 0.5980 |
| 0.492 | 4.0 | 1640 | 0.7309 | 0.6240 |
| 0.39 | 5.0 | 2050 | 0.8072 | 0.6134 |
| 0.2999 | 6.0 | 2460 | 0.9768 | 0.6116 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3