---
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: 0.2755
- Precision: 0.4545
- Recall: 0.0935
- F1: 0.1550
- Accuracy: 0.9109

## 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3038        | 0.4292 | 100  | 0.2895          | 0.0       | 0.0    | 0.0    | 0.9125   |
| 0.2835        | 0.8584 | 200  | 0.2731          | 0.0       | 0.0    | 0.0    | 0.9125   |
| 0.2383        | 1.2876 | 300  | 0.2710          | 0.5606    | 0.0384 | 0.0719 | 0.9132   |
| 0.2385        | 1.7167 | 400  | 0.2685          | 0.6786    | 0.0197 | 0.0383 | 0.9134   |
| 0.2356        | 2.1459 | 500  | 0.2734          | 0.4466    | 0.0955 | 0.1574 | 0.9105   |
| 0.2067        | 2.5751 | 600  | 0.2719          | 0.4703    | 0.0987 | 0.1631 | 0.9114   |


### Framework versions

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