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--- |
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library_name: transformers |
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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: pretrain_model |
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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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# pretrain_model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6409 |
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- Precision: 0.6385 |
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- Recall: 0.6046 |
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- F1: 0.6211 |
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- Accuracy: 0.6354 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.6994 | 0.0061 | 250 | 0.6909 | 0.5946 | 0.1740 | 0.2692 | 0.5296 | |
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| 0.6935 | 0.0122 | 500 | 0.6461 | 0.6368 | 0.5923 | 0.6138 | 0.6288 | |
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| 0.6862 | 0.0184 | 750 | 0.6710 | 0.6268 | 0.6416 | 0.6341 | 0.6313 | |
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| 0.6629 | 0.0245 | 1000 | 0.8414 | 0.5772 | 0.7777 | 0.6626 | 0.6056 | |
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| 0.6729 | 0.0306 | 1250 | 0.6509 | 0.6373 | 0.5992 | 0.6177 | 0.6306 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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