---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 2504separado5
  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. -->

# 2504separado5

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6571
- Accuracy: 0.8487
- Precision: 0.8491
- Recall: 0.8487
- F1: 0.8487
- Ratio: 0.5168

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 4
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.3101        | 0.9870 | 38   | 0.7275          | 0.8445   | 0.8465    | 0.8445 | 0.8443 | 0.4622 |
| 0.3189        | 2.0    | 77   | 0.7399          | 0.8445   | 0.8448    | 0.8445 | 0.8445 | 0.5126 |
| 0.3786        | 2.9870 | 115  | 0.7200          | 0.8361   | 0.8390    | 0.8361 | 0.8358 | 0.5462 |
| 0.3816        | 3.9481 | 152  | 0.6571          | 0.8487   | 0.8491    | 0.8487 | 0.8487 | 0.5168 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1