
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# email_question_extraction

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0071
- Precision: 0.4595
- Recall: 0.8095
- F1: 0.5862
- Accuracy: 0.9978

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0653        | 1.0   | 73   | 0.0097          | 0.5156    | 0.7857 | 0.6226 | 0.9963   |
| 0.0307        | 2.0   | 146  | 0.0056          | 0.5263    | 0.7143 | 0.6061 | 0.9986   |
| 0.027         | 3.0   | 219  | 0.0081          | 0.4667    | 0.8333 | 0.5983 | 0.9971   |
| 0.0046        | 4.0   | 292  | 0.0071          | 0.4595    | 0.8095 | 0.5862 | 0.9978   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.16.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "roberta-base", "model-index": [{"name": "email_question_extraction", "results": []}]}
transformers safetensors roberta token-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us