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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: 0.1217 |
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- Precision: 0.3878 |
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- Recall: 0.7037 |
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- F1: 0.5 |
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- Accuracy: 0.9781 |
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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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| 0.398 | 1.0 | 30 | 0.1426 | 0.1493 | 0.3704 | 0.2128 | 0.9649 | |
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| 0.1839 | 2.0 | 60 | 0.1316 | 0.2453 | 0.4815 | 0.325 | 0.9699 | |
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| 0.1011 | 3.0 | 90 | 0.1125 | 0.3878 | 0.7037 | 0.5 | 0.9779 | |
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| 0.1296 | 4.0 | 120 | 0.1217 | 0.3878 | 0.7037 | 0.5 | 0.9781 | |
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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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