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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: training-1 |
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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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# training-1 |
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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: 0.0448 |
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- Accuracy: 0.9937 |
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- Precision: 0.9912 |
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- Recall: 0.9859 |
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- F1: 0.9885 |
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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: 1e-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: 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.5 | 302 | 0.0546 | 0.9870 | 0.9737 | 0.9789 | 0.9763 | |
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| No log | 1.0 | 604 | 0.0511 | 0.9913 | 0.9911 | 0.9771 | 0.9840 | |
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| 0.1032 | 1.5 | 906 | 0.0558 | 0.9899 | 0.9807 | 0.9824 | 0.9815 | |
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| 0.1032 | 2.0 | 1208 | 0.0467 | 0.9928 | 0.9982 | 0.9754 | 0.9866 | |
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| 0.0353 | 2.5 | 1510 | 0.0411 | 0.9937 | 0.9929 | 0.9842 | 0.9885 | |
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| 0.0353 | 3.0 | 1812 | 0.0460 | 0.9932 | 0.9911 | 0.9842 | 0.9876 | |
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| 0.0183 | 3.49 | 2114 | 0.0423 | 0.9937 | 0.9947 | 0.9824 | 0.9885 | |
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| 0.0183 | 3.99 | 2416 | 0.0476 | 0.9932 | 0.9911 | 0.9842 | 0.9876 | |
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| 0.013 | 4.49 | 2718 | 0.0463 | 0.9932 | 0.9911 | 0.9842 | 0.9876 | |
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| 0.013 | 4.99 | 3020 | 0.0448 | 0.9937 | 0.9912 | 0.9859 | 0.9885 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.2.0.dev20230913+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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