---
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: 080524_epoch_13
  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. -->

# 080524_epoch_13

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: 0.8371
- Accuracy: 0.8151
- Precision: 0.8509
- Recall: 0.8151
- F1: 0.8103
- Ratio: 0.6597

## 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: 10
- eval_batch_size: 2
- seed: 47
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- lr_scheduler_warmup_steps: 4
- num_epochs: 1
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.3002        | 0.1176 | 10   | 0.8662          | 0.8151   | 0.8509    | 0.8151 | 0.8103 | 0.6597 |
| 0.3026        | 0.2353 | 20   | 0.7930          | 0.8277   | 0.8516    | 0.8277 | 0.8248 | 0.6303 |
| 0.2933        | 0.3529 | 30   | 0.7946          | 0.8277   | 0.8484    | 0.8277 | 0.8251 | 0.6218 |
| 0.2921        | 0.4706 | 40   | 0.8687          | 0.8151   | 0.8509    | 0.8151 | 0.8103 | 0.6597 |
| 0.2947        | 0.5882 | 50   | 0.8540          | 0.8109   | 0.8442    | 0.8109 | 0.8062 | 0.6555 |
| 0.3148        | 0.7059 | 60   | 0.8454          | 0.8151   | 0.8469    | 0.8151 | 0.8108 | 0.6513 |
| 0.3221        | 0.8235 | 70   | 0.8642          | 0.8151   | 0.8509    | 0.8151 | 0.8103 | 0.6597 |
| 0.316         | 0.9412 | 80   | 0.8389          | 0.8151   | 0.8509    | 0.8151 | 0.8103 | 0.6597 |


### Framework versions

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