---
library_name: transformers
license: mit
base_model: 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 [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8504
- Precision: 0.2663
- Recall: 0.2503
- F1: 0.2580
- Accuracy: 0.8740

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0738        | 0.4292 | 100  | 3.5742          | 0.3714    | 0.1080 | 0.1673 | 0.9059   |
| 0.0518        | 0.8584 | 200  | 3.6916          | 0.4130    | 0.1059 | 0.1686 | 0.9086   |
| 0.0464        | 1.2876 | 300  | 2.9332          | 0.3185    | 0.2461 | 0.2777 | 0.8879   |
| 0.0313        | 1.7167 | 400  | 3.4018          | 0.3495    | 0.1568 | 0.2165 | 0.9007   |
| 0.0262        | 2.1459 | 500  | 3.6431          | 0.3581    | 0.1599 | 0.2211 | 0.9014   |
| 0.0374        | 2.5751 | 600  | 3.2736          | 0.3184    | 0.2139 | 0.2559 | 0.8911   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0