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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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- 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: email_question_extraction |
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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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# email_question_extraction |
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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: 0.0071 |
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- Precision: 0.4595 |
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- Recall: 0.8095 |
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- F1: 0.5862 |
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- Accuracy: 0.9978 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 4 |
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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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| 0.0653 | 1.0 | 73 | 0.0097 | 0.5156 | 0.7857 | 0.6226 | 0.9963 | |
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| 0.0307 | 2.0 | 146 | 0.0056 | 0.5263 | 0.7143 | 0.6061 | 0.9986 | |
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| 0.027 | 3.0 | 219 | 0.0081 | 0.4667 | 0.8333 | 0.5983 | 0.9971 | |
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| 0.0046 | 4.0 | 292 | 0.0071 | 0.4595 | 0.8095 | 0.5862 | 0.9978 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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