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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-large |
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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: Openn_binary |
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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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# Openn_binary |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6757 |
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- Accuracy: 0.6729 |
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- Precision: 0.7201 |
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- Recall: 0.6050 |
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- F1: 0.6576 |
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- Auc: 0.6756 |
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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: 32 |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| No log | 1.0 | 134 | 0.6469 | 0.6440 | 0.6476 | 0.6894 | 0.6678 | 0.6422 | |
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| No log | 2.0 | 268 | 0.6340 | 0.6598 | 0.7667 | 0.4955 | 0.6020 | 0.6664 | |
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| No log | 3.0 | 402 | 0.6757 | 0.6729 | 0.7201 | 0.6050 | 0.6576 | 0.6756 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.19.1 |
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