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---
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
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