bert-base-uncased-finetuned-rte-run_3
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0373
- Accuracy: 0.6968
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: 64
- eval_batch_size: 32
- seed: 42
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6504 | 1.0 | 39 | 0.6453 | 0.6390 |
| 0.5147 | 2.0 | 78 | 0.7127 | 0.6895 |
| 0.2888 | 3.0 | 117 | 0.6918 | 0.7004 |
| 0.1676 | 4.0 | 156 | 0.8771 | 0.7040 |
| 0.0967 | 5.0 | 195 | 1.0373 | 0.6968 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1