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disfluency-large-2
This model is a fine-tuned version of vinai/phobert-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0318
- Precision: 0.9837
- Recall: 0.9808
- F1: 0.9822
- Accuracy: 0.9946
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 140 | 0.0439 | 0.9538 | 0.9561 | 0.9550 | 0.9890 |
| No log | 2.0 | 280 | 0.0314 | 0.9660 | 0.9736 | 0.9698 | 0.9906 |
| No log | 3.0 | 420 | 0.0394 | 0.9710 | 0.9651 | 0.9681 | 0.9909 |
| 0.1105 | 4.0 | 560 | 0.0320 | 0.9795 | 0.9784 | 0.9790 | 0.9929 |
| 0.1105 | 5.0 | 700 | 0.0450 | 0.9704 | 0.9657 | 0.9681 | 0.9904 |
| 0.1105 | 6.0 | 840 | 0.0463 | 0.9776 | 0.9694 | 0.9734 | 0.9911 |
| 0.1105 | 7.0 | 980 | 0.0480 | 0.9706 | 0.9712 | 0.9709 | 0.9909 |
| 0.0113 | 8.0 | 1120 | 0.0318 | 0.9837 | 0.9808 | 0.9822 | 0.9946 |
| 0.0113 | 9.0 | 1260 | 0.0419 | 0.9699 | 0.9669 | 0.9684 | 0.9915 |
| 0.0113 | 10.0 | 1400 | 0.0458 | 0.9735 | 0.9712 | 0.9723 | 0.9920 |
| 0.0051 | 11.0 | 1540 | 0.0309 | 0.9777 | 0.9766 | 0.9771 | 0.9935 |
| 0.0051 | 12.0 | 1680 | 0.0232 | 0.9820 | 0.9820 | 0.9820 | 0.9951 |
| 0.0051 | 13.0 | 1820 | 0.0344 | 0.9849 | 0.9784 | 0.9816 | 0.9945 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
