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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: roberta-base_gpt-4o-2024-05-13_gpt-4o-mini-2024-07-18_20240913_044355 |
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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_gpt-4o-2024-05-13_gpt-4o-mini-2024-07-18_20240913_044355 |
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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: 0.4503 |
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- Accuracy: 0.8026 |
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- F1: 0.8832 |
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- Precision: 0.8292 |
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- Recall: 0.9448 |
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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: 8 |
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- seed: 420 |
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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 | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4781 | 1.0 | 871 | 0.4503 | 0.8026 | 0.8832 | 0.8292 | 0.9448 | |
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| 0.4526 | 2.0 | 1742 | 0.4536 | 0.8048 | 0.8822 | 0.8434 | 0.9248 | |
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| 0.424 | 3.0 | 2613 | 0.4529 | 0.8052 | 0.8837 | 0.8362 | 0.9370 | |
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| 0.3789 | 4.0 | 3484 | 0.4970 | 0.8029 | 0.8826 | 0.8336 | 0.9379 | |
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| 0.3275 | 5.0 | 4355 | 0.5587 | 0.7945 | 0.8777 | 0.8286 | 0.9330 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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