---
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: 0.5440
- Precision: 0.3143
- Recall: 0.2170
- F1: 0.2568
- Accuracy: 0.8900

## 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2733        | 0.4292 | 100  | 0.4491          | 0.3382    | 0.1454 | 0.2033 | 0.9003   |
| 0.2635        | 0.8584 | 200  | 0.4566          | 0.3327    | 0.1848 | 0.2377 | 0.8962   |
| 0.202         | 1.2876 | 300  | 0.5266          | 0.3377    | 0.1599 | 0.2171 | 0.8990   |
| 0.1981        | 1.7167 | 400  | 0.5384          | 0.3529    | 0.1495 | 0.2101 | 0.9016   |
| 0.1904        | 2.1459 | 500  | 0.5169          | 0.3004    | 0.2399 | 0.2667 | 0.8846   |
| 0.1682        | 2.5751 | 600  | 0.5660          | 0.3339    | 0.1963 | 0.2472 | 0.8954   |


### Framework versions

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