---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: FS_25_05
  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. -->

# FS_25_05

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1403
- Accuracy: 0.9745
- Precision: 0.9751
- Recall: 0.9743
- F1: 0.9744
- Ratio: 0.0529

## 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: 8
- eval_batch_size: 8
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 1.7313        | 1.0   | 362  | 1.5891          | 0.9137   | 0.9237    | 0.9138 | 0.9148 | 0.0569 |
| 0.3284        | 2.0   | 724  | 0.2812          | 0.9529   | 0.9560    | 0.9528 | 0.9533 | 0.0490 |
| 0.103         | 3.0   | 1086 | 0.1580          | 0.9667   | 0.9681    | 0.9665 | 0.9663 | 0.0510 |
| 0.1073        | 4.0   | 1448 | 0.1532          | 0.9686   | 0.9693    | 0.9685 | 0.9686 | 0.0529 |
| 0.1295        | 5.0   | 1810 | 0.1403          | 0.9745   | 0.9751    | 0.9743 | 0.9744 | 0.0529 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1