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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: roberta-base-downstream-build_rr |
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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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# roberta-base-downstream-build_rr |
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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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- Precision: 0.1983 |
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- Recall: 0.3587 |
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- F1: 0.2554 |
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- Micro-f1: 0.2554 |
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- Accuracy: 0.9191 |
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- Loss: 0.2640 |
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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: 3e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 1 |
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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: 20.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Precision | Recall | F1 | Micro-f1 | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------:|:------:|:------:|:--------:|:--------:|:---------------:| |
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| No log | 1.0 | 62 | 0.0835 | 0.1152 | 0.0968 | 0.0968 | 0.8780 | 0.4226 | |
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| No log | 2.0 | 124 | 0.1537 | 0.2696 | 0.1957 | 0.1957 | 0.8931 | 0.3475 | |
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| No log | 3.0 | 186 | 0.1875 | 0.3391 | 0.2415 | 0.2415 | 0.9052 | 0.2912 | |
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| No log | 4.0 | 248 | 0.1992 | 0.3304 | 0.2486 | 0.2486 | 0.9003 | 0.2991 | |
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| No log | 5.0 | 310 | 0.1784 | 0.3870 | 0.2442 | 0.2442 | 0.9066 | 0.2833 | |
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| No log | 6.0 | 372 | 0.2206 | 0.3543 | 0.2719 | 0.2719 | 0.9148 | 0.2642 | |
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| No log | 7.0 | 434 | 0.2300 | 0.3630 | 0.2816 | 0.2816 | 0.9177 | 0.2584 | |
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| No log | 8.0 | 496 | 0.2179 | 0.3696 | 0.2742 | 0.2742 | 0.9177 | 0.2523 | |
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| 0.4245 | 9.0 | 558 | 0.1921 | 0.3696 | 0.2528 | 0.2528 | 0.9167 | 0.2630 | |
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| 0.4245 | 10.0 | 620 | 0.1983 | 0.3587 | 0.2554 | 0.2554 | 0.9191 | 0.2640 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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