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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: output |
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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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# output |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7144 |
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- Precision: 0.9059 |
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- Recall: 0.9049 |
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- Accuracy: 0.9049 |
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- F1-score: 0.9053 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:| |
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| 0.6607 | 1.0 | 309 | 0.3826 | 0.8915 | 0.8907 | 0.8907 | 0.8905 | |
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| 0.2673 | 2.0 | 618 | 0.4694 | 0.8886 | 0.8866 | 0.8866 | 0.8860 | |
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| 0.1819 | 3.0 | 927 | 0.4766 | 0.9001 | 0.8988 | 0.8988 | 0.8989 | |
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| 0.102 | 4.0 | 1236 | 0.6096 | 0.8945 | 0.8927 | 0.8927 | 0.8930 | |
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| 0.0607 | 5.0 | 1545 | 0.6537 | 0.8971 | 0.8947 | 0.8947 | 0.8955 | |
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| 0.0326 | 6.0 | 1854 | 0.6568 | 0.9127 | 0.9109 | 0.9109 | 0.9116 | |
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| 0.0221 | 7.0 | 2163 | 0.7081 | 0.9045 | 0.9028 | 0.9028 | 0.9035 | |
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| 0.0133 | 8.0 | 2472 | 0.7144 | 0.9059 | 0.9049 | 0.9049 | 0.9053 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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