test_trainer
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1535
- Accuracy: 0.846
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 63 | 0.4610 | 0.818 |
| No log | 2.0 | 126 | 0.6583 | 0.828 |
| No log | 3.0 | 189 | 0.6051 | 0.848 |
| No log | 4.0 | 252 | 0.9601 | 0.83 |
| No log | 5.0 | 315 | 0.8297 | 0.858 |
| No log | 6.0 | 378 | 0.9417 | 0.866 |
| No log | 7.0 | 441 | 0.9992 | 0.86 |
| 0.1794 | 8.0 | 504 | 1.1292 | 0.846 |
| 0.1794 | 9.0 | 567 | 1.1538 | 0.842 |
| 0.1794 | 10.0 | 630 | 1.1535 | 0.846 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 3
Model tree for st25/test_trainer
Base model
google-bert/bert-base-cased