bert-action-ro
This model is a fine-tuned version of bert-base-cased on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1567
- Accuracy: 0.958
- Precision: 0.949
- Recall: 0.941
- F1: 0.944
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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
Precision |
Recall |
F1 |
| No log |
1.0 |
89 |
0.3700 |
0.876 |
0.836 |
0.809 |
0.815 |
| No log |
2.0 |
178 |
0.2057 |
0.936 |
0.927 |
0.924 |
0.924 |
| No log |
3.0 |
267 |
0.1567 |
0.958 |
0.949 |
0.941 |
0.944 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
