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--- |
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license: mit |
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base_model: tangminhanh/ts_tg |
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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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- precision |
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- recall |
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model-index: |
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- name: ts_cate |
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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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# ts_cate |
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This model is a fine-tuned version of [tangminhanh/ts_tg](https://huggingface.co/tangminhanh/ts_tg) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0263 |
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- Accuracy: 0.8555 |
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- F1: 0.8736 |
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- Precision: 0.8824 |
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- Recall: 0.8649 |
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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: 32 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 404 | 0.0458 | 0.6802 | 0.7650 | 0.8750 | 0.6796 | |
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| 0.1001 | 2.0 | 808 | 0.0318 | 0.7717 | 0.8259 | 0.8817 | 0.7767 | |
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| 0.0321 | 3.0 | 1212 | 0.0278 | 0.8251 | 0.8564 | 0.8862 | 0.8286 | |
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| 0.0215 | 4.0 | 1616 | 0.0256 | 0.8322 | 0.8627 | 0.8909 | 0.8363 | |
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| 0.0161 | 5.0 | 2020 | 0.0256 | 0.8455 | 0.8679 | 0.8812 | 0.8551 | |
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| 0.0161 | 6.0 | 2424 | 0.0259 | 0.8499 | 0.8711 | 0.8831 | 0.8594 | |
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| 0.0124 | 7.0 | 2828 | 0.0255 | 0.8536 | 0.8713 | 0.8836 | 0.8594 | |
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| 0.0105 | 8.0 | 3232 | 0.0262 | 0.8533 | 0.8723 | 0.8836 | 0.8612 | |
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| 0.0087 | 9.0 | 3636 | 0.0261 | 0.8567 | 0.8746 | 0.8838 | 0.8656 | |
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| 0.0078 | 10.0 | 4040 | 0.0263 | 0.8555 | 0.8736 | 0.8824 | 0.8649 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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