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--- |
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base_model: vinai/phobert-base-v2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: metadata-cls-no-gov-8k-v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenducbao/huggingface/runs/s6iy3mkr) |
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# metadata-cls-no-gov-8k-v2 |
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3052 |
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- Accuracy: 0.9447 |
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- F1: 0.7927 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
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| 0.5649 | 1.6260 | 200 | 0.2215 | 0.9455 | 0.7479 | |
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| 0.1634 | 3.2520 | 400 | 0.1869 | 0.9438 | 0.8204 | |
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| 0.1222 | 4.8780 | 600 | 0.2286 | 0.9370 | 0.7837 | |
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| 0.0808 | 6.5041 | 800 | 0.2174 | 0.9532 | 0.8263 | |
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| 0.0528 | 8.1301 | 1000 | 0.2440 | 0.9387 | 0.7862 | |
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| 0.046 | 9.7561 | 1200 | 0.2416 | 0.9472 | 0.8180 | |
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| 0.0329 | 11.3821 | 1400 | 0.2631 | 0.9464 | 0.7967 | |
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| 0.0271 | 13.0081 | 1600 | 0.2769 | 0.9481 | 0.8124 | |
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| 0.0179 | 14.6341 | 1800 | 0.2687 | 0.9506 | 0.8122 | |
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| 0.0185 | 16.2602 | 2000 | 0.2935 | 0.9438 | 0.7921 | |
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| 0.0153 | 17.8862 | 2200 | 0.2957 | 0.9455 | 0.7907 | |
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| 0.0146 | 19.5122 | 2400 | 0.3052 | 0.9447 | 0.7927 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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