| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: disfluency-large |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # disfluency-large |
|
|
| This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0438 |
| - Precision: 0.9698 |
| - Recall: 0.9663 |
| - F1: 0.9681 |
| - Accuracy: 0.9921 |
|
|
| ## 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: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 140 | 0.0422 | 0.9651 | 0.9627 | 0.9639 | 0.9902 | |
| | No log | 2.0 | 280 | 0.0315 | 0.9718 | 0.9730 | 0.9724 | 0.9923 | |
| | No log | 3.0 | 420 | 0.2221 | 0.8079 | 0.7530 | 0.7795 | 0.9355 | |
| | 0.024 | 4.0 | 560 | 0.0379 | 0.9693 | 0.9675 | 0.9684 | 0.9926 | |
| | 0.024 | 5.0 | 700 | 0.0499 | 0.9657 | 0.9639 | 0.9648 | 0.9905 | |
| | 0.024 | 6.0 | 840 | 0.0388 | 0.9688 | 0.9688 | 0.9688 | 0.9925 | |
| | 0.024 | 7.0 | 980 | 0.0438 | 0.9698 | 0.9663 | 0.9681 | 0.9921 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.27.4 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
|
|
