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--- |
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license: mit |
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base_model: roberta-base |
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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: fintunned-v2-roberta |
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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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# fintunned-v2-roberta |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2012 |
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- Accuracy: 0.95 |
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- F1: 0.9504 |
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- Precision: 0.9517 |
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- Recall: 0.9498 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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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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| 2.3929 | 0.45 | 50 | 2.2723 | 0.2773 | 0.1892 | 0.2335 | 0.2947 | |
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| 1.2165 | 0.91 | 100 | 0.4612 | 0.8818 | 0.8839 | 0.8978 | 0.8825 | |
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| 0.3732 | 1.36 | 150 | 0.3472 | 0.9045 | 0.9058 | 0.9092 | 0.9060 | |
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| 0.3306 | 1.82 | 200 | 0.3077 | 0.9227 | 0.9249 | 0.9267 | 0.9250 | |
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| 0.2537 | 2.27 | 250 | 0.2419 | 0.9273 | 0.9281 | 0.9290 | 0.9291 | |
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| 0.0997 | 2.73 | 300 | 0.2012 | 0.95 | 0.9504 | 0.9517 | 0.9498 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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