---
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_1
  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_1

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: 0.7794
- Accuracy: 0.7395
- Precision: 0.7816
- Recall: 0.7395
- F1: 0.7294
- Ratio: 0.6933

## 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  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 3.1579        | 0.1176 | 10   | 2.2074          | 0.5126   | 0.5335    | 0.5126 | 0.4225 | 0.8950 |
| 1.5576        | 0.2353 | 20   | 1.3600          | 0.5504   | 0.5760    | 0.5504 | 0.5092 | 0.2101 |
| 1.1011        | 0.3529 | 30   | 0.9525          | 0.5588   | 0.5625    | 0.5588 | 0.5522 | 0.6218 |
| 0.9083        | 0.4706 | 40   | 0.8505          | 0.6471   | 0.6471    | 0.6471 | 0.6470 | 0.5084 |
| 0.8014        | 0.5882 | 50   | 0.8729          | 0.6765   | 0.7659    | 0.6765 | 0.6468 | 0.7899 |
| 0.7514        | 0.7059 | 60   | 0.7322          | 0.7563   | 0.7610    | 0.7563 | 0.7552 | 0.5672 |
| 0.7259        | 0.8235 | 70   | 0.7631          | 0.7437   | 0.7730    | 0.7437 | 0.7366 | 0.6639 |
| 0.7605        | 0.9412 | 80   | 0.7794          | 0.7395   | 0.7816    | 0.7395 | 0.7294 | 0.6933 |


### Framework versions

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