---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model
  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. -->

# model

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6917
- Precision: 0.7168
- Recall: 0.7053
- F1: 0.7088
- Accuracy: 0.726

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.9791        | 1.0   | 1489 | 0.8084          | 0.6198    | 0.6089 | 0.6093 | 0.6385   |
| 0.8129        | 2.0   | 2978 | 0.7380          | 0.6635    | 0.6500 | 0.6531 | 0.6735   |
| 0.6937        | 3.0   | 4467 | 0.7328          | 0.6826    | 0.6716 | 0.6745 | 0.691    |
| 0.6002        | 4.0   | 5956 | 0.6901          | 0.7110    | 0.6951 | 0.6973 | 0.7205   |
| 0.5362        | 5.0   | 7445 | 0.6917          | 0.7168    | 0.7053 | 0.7088 | 0.726    |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1