---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: email_question_extraction
  results: []
---

<!-- 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: 0.1217
- Precision: 0.3878
- Recall: 0.7037
- F1: 0.5
- Accuracy: 0.9781

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


### Framework versions

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