---
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: 060524_epoch_2
  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. -->

# 060524_epoch_2

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: 0.6952
- Accuracy: 0.7437
- Precision: 0.7569
- Recall: 0.7437
- F1: 0.7404
- Ratio: 0.6134

## 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: 42
- 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  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.7924        | 0.1626 | 10   | 0.7754          | 0.7101   | 0.7233    | 0.7101 | 0.7057 | 0.3782 |
| 0.641         | 0.3252 | 20   | 0.8257          | 0.7227   | 0.7451    | 0.7227 | 0.7162 | 0.6513 |
| 0.8108        | 0.4878 | 30   | 0.7629          | 0.7563   | 0.7564    | 0.7563 | 0.7563 | 0.4916 |
| 0.736         | 0.6504 | 40   | 0.7167          | 0.7731   | 0.7751    | 0.7731 | 0.7727 | 0.4580 |
| 0.6973        | 0.8130 | 50   | 0.7419          | 0.7143   | 0.7448    | 0.7143 | 0.7051 | 0.6765 |
| 0.7981        | 0.9756 | 60   | 0.6962          | 0.7437   | 0.7569    | 0.7437 | 0.7404 | 0.6134 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1