---
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_27_06_normal
  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_27_06_normal

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: 0.1484
- Accuracy: 0.97
- Precision: 0.9713
- Recall: 0.97
- F1: 0.9701

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7048        | 1.0   | 375  | 1.5380          | 0.948    | 0.9492    | 0.9480 | 0.9480 |
| 0.1844        | 2.0   | 750  | 0.2731          | 0.954    | 0.9597    | 0.9540 | 0.9550 |
| 0.1253        | 3.0   | 1125 | 0.1484          | 0.97     | 0.9713    | 0.97   | 0.9701 |
| 0.0213        | 4.0   | 1500 | 0.1617          | 0.97     | 0.9715    | 0.9700 | 0.9701 |
| 0.0175        | 5.0   | 1875 | 0.1521          | 0.974    | 0.9749    | 0.974  | 0.9740 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1