---
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
  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

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: 0.1744
- Accuracy: 0.966
- Precision: 0.9668
- Recall: 0.966
- F1: 0.9660

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6727        | 1.0   | 375  | 1.5301          | 0.93     | 0.9351    | 0.9300 | 0.9300 |
| 0.2375        | 2.0   | 750  | 0.2548          | 0.958    | 0.9622    | 0.958  | 0.9583 |
| 0.1424        | 3.0   | 1125 | 0.1922          | 0.96     | 0.9612    | 0.9600 | 0.9599 |
| 0.0197        | 4.0   | 1500 | 0.1789          | 0.966    | 0.9670    | 0.966  | 0.9660 |
| 0.0171        | 5.0   | 1875 | 0.1744          | 0.966    | 0.9668    | 0.966  | 0.9660 |


### Framework versions

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