---
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_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_25_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: 0.1755
- Accuracy: 0.9647
- Precision: 0.9651
- Recall: 0.9646
- F1: 0.9644
- 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  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 1.7815        | 1.0   | 362  | 1.6483          | 0.9059   | 0.9166    | 0.9061 | 0.9069 | 0.0569 |
| 0.364         | 2.0   | 724  | 0.2948          | 0.9451   | 0.9480    | 0.9450 | 0.9447 | 0.0569 |
| 0.0418        | 3.0   | 1086 | 0.2467          | 0.9510   | 0.9529    | 0.9509 | 0.9509 | 0.0549 |
| 0.0218        | 4.0   | 1448 | 0.1853          | 0.9647   | 0.9651    | 0.9646 | 0.9644 | 0.0529 |
| 0.0985        | 5.0   | 1810 | 0.1755          | 0.9647   | 0.9651    | 0.9646 | 0.9644 | 0.0529 |


### Framework versions

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