---
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: 1.1545
- Precision: 0.2718
- Recall: 0.2523
- F1: 0.2617
- Accuracy: 0.8754

## 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1562        | 0.4292 | 100  | 1.0438          | 0.3433    | 0.1900 | 0.2447 | 0.8973   |
| 0.1346        | 0.8584 | 200  | 1.0574          | 0.3029    | 0.2305 | 0.2618 | 0.8862   |
| 0.1116        | 1.2876 | 300  | 1.4601          | 0.4197    | 0.1194 | 0.1859 | 0.9085   |
| 0.1141        | 1.7167 | 400  | 1.0446          | 0.2705    | 0.2565 | 0.2633 | 0.8744   |
| 0.1047        | 2.1459 | 500  | 1.1404          | 0.2783    | 0.2710 | 0.2746 | 0.8747   |
| 0.103         | 2.5751 | 600  | 1.3562          | 0.3015    | 0.1869 | 0.2308 | 0.8909   |


### Framework versions

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