---
base_model: textattack/roberta-base-ag-news
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base-ag-news
  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. -->

# roberta-base-ag-news

This model is a fine-tuned version of [textattack/roberta-base-ag-news](https://huggingface.co/textattack/roberta-base-ag-news) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2492
- Accuracy: 0.9457
- F1: 0.9456
- Precision: 0.9456
- Recall: 0.9457

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.073         | 1.0   | 3750 | 0.2088          | 0.9417   | 0.9416 | 0.9419    | 0.9417 |
| 0.0576        | 2.0   | 7500 | 0.2492          | 0.9457   | 0.9456 | 0.9456    | 0.9457 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1