---
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_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. -->

# 080524_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: 0.6633
- Accuracy: 0.7941
- Precision: 0.8018
- Recall: 0.7941
- F1: 0.7928
- Ratio: 0.5798

## 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  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.8337        | 0.1626 | 10   | 0.7759          | 0.7101   | 0.7126    | 0.7101 | 0.7092 | 0.4454 |
| 0.7644        | 0.3252 | 20   | 0.7252          | 0.7563   | 0.7654    | 0.7563 | 0.7542 | 0.5924 |
| 0.7339        | 0.4878 | 30   | 0.6925          | 0.7689   | 0.7732    | 0.7689 | 0.7680 | 0.5630 |
| 0.7102        | 0.6504 | 40   | 0.6907          | 0.7647   | 0.7802    | 0.7647 | 0.7614 | 0.6176 |
| 0.7758        | 0.8130 | 50   | 0.6682          | 0.7857   | 0.7917    | 0.7857 | 0.7846 | 0.5714 |
| 0.6621        | 0.9756 | 60   | 0.6632          | 0.7899   | 0.7967    | 0.7899 | 0.7887 | 0.5756 |


### Framework versions

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