bert-finetuned-tv-dim
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1605
- Precision: 0.75
- Recall: 0.7875
- F1: 0.7683
- Accuracy: 0.9492
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|
| No log | 1.0 | 25 | 0.1561 | 0.7195 | 0.7375 | 0.7284 | 0.9423 |
| No log | 2.0 | 50 | 0.1572 | 0.7412 | 0.7875 | 0.7636 | 0.9464 |
| No log | 3.0 | 75 | 0.1605 | 0.75 | 0.7875 | 0.7683 | 0.9492 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
