| --- |
| base_model: vinai/phobert-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: CS505-Classifier-T4_predictLabel_a1 |
| 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. --> |
|
|
| # CS505-Classifier-T4_predictLabel_a1 |
|
|
| This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0155 |
|
|
| ## 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: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | No log | 0.98 | 48 | 1.0473 | |
| | No log | 1.96 | 96 | 0.5664 | |
| | No log | 2.94 | 144 | 0.3371 | |
| | No log | 3.92 | 192 | 0.2277 | |
| | No log | 4.9 | 240 | 0.1850 | |
| | No log | 5.88 | 288 | 0.1451 | |
| | No log | 6.86 | 336 | 0.1126 | |
| | No log | 7.84 | 384 | 0.0853 | |
| | No log | 8.82 | 432 | 0.0635 | |
| | No log | 9.8 | 480 | 0.0598 | |
| | 0.4029 | 10.78 | 528 | 0.0407 | |
| | 0.4029 | 11.76 | 576 | 0.0337 | |
| | 0.4029 | 12.73 | 624 | 0.0300 | |
| | 0.4029 | 13.71 | 672 | 0.0270 | |
| | 0.4029 | 14.69 | 720 | 0.0209 | |
| | 0.4029 | 15.67 | 768 | 0.0196 | |
| | 0.4029 | 16.65 | 816 | 0.0205 | |
| | 0.4029 | 17.63 | 864 | 0.0181 | |
| | 0.4029 | 18.61 | 912 | 0.0160 | |
| | 0.4029 | 19.59 | 960 | 0.0155 | |
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| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
