---
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_5
  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_5

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: 0.3399
- Accuracy: 0.981
- Precision: 0.9810
- Recall: 0.981
- F1: 0.9810
- Ratio: 0.495

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----:|
| 0.3013        | 0.0333 | 10   | 0.3474          | 0.978    | 0.9783    | 0.978  | 0.9780 | 0.488 |
| 0.3087        | 0.0667 | 20   | 0.3471          | 0.979    | 0.9790    | 0.979  | 0.9790 | 0.495 |
| 0.3181        | 0.1    | 30   | 0.3527          | 0.975    | 0.9752    | 0.975  | 0.9750 | 0.489 |
| 0.3134        | 0.1333 | 40   | 0.3602          | 0.971    | 0.9714    | 0.971  | 0.9710 | 0.485 |
| 0.3002        | 0.1667 | 50   | 0.3481          | 0.979    | 0.9790    | 0.979  | 0.9790 | 0.501 |
| 0.3226        | 0.2    | 60   | 0.3547          | 0.978    | 0.9780    | 0.978  | 0.9780 | 0.496 |
| 0.2919        | 0.2333 | 70   | 0.3687          | 0.972    | 0.9724    | 0.972  | 0.9720 | 0.486 |
| 0.2932        | 0.2667 | 80   | 0.3822          | 0.965    | 0.9664    | 0.965  | 0.9650 | 0.473 |
| 0.3303        | 0.3    | 90   | 0.3754          | 0.969    | 0.9700    | 0.969  | 0.9690 | 0.477 |
| 0.3162        | 0.3333 | 100  | 0.3557          | 0.975    | 0.9750    | 0.975  | 0.9750 | 0.505 |
| 0.3012        | 0.3667 | 110  | 0.3554          | 0.974    | 0.9741    | 0.974  | 0.9740 | 0.506 |
| 0.3337        | 0.4    | 120  | 0.3629          | 0.972    | 0.9725    | 0.972  | 0.9720 | 0.484 |
| 0.3007        | 0.4333 | 130  | 0.3492          | 0.979    | 0.9792    | 0.979  | 0.9790 | 0.491 |
| 0.3283        | 0.4667 | 140  | 0.3467          | 0.979    | 0.9790    | 0.979  | 0.9790 | 0.495 |
| 0.3238        | 0.5    | 150  | 0.3410          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.497 |
| 0.3076        | 0.5333 | 160  | 0.3387          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.498 |
| 0.3348        | 0.5667 | 170  | 0.3375          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.498 |
| 0.3258        | 0.6    | 180  | 0.3401          | 0.98     | 0.9801    | 0.98   | 0.9800 | 0.494 |
| 0.3195        | 0.6333 | 190  | 0.3424          | 0.978    | 0.9781    | 0.978  | 0.9780 | 0.492 |
| 0.31          | 0.6667 | 200  | 0.3392          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.495 |
| 0.3407        | 0.7    | 210  | 0.3393          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.502 |
| 0.3494        | 0.7333 | 220  | 0.3413          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.501 |
| 0.3574        | 0.7667 | 230  | 0.3402          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.496 |
| 0.3379        | 0.8    | 240  | 0.3385          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.496 |
| 0.3532        | 0.8333 | 250  | 0.3385          | 0.982    | 0.9820    | 0.982  | 0.9820 | 0.496 |
| 0.318         | 0.8667 | 260  | 0.3425          | 0.98     | 0.9801    | 0.98   | 0.9800 | 0.494 |
| 0.3475        | 0.9    | 270  | 0.3432          | 0.98     | 0.9801    | 0.98   | 0.9800 | 0.494 |
| 0.3142        | 0.9333 | 280  | 0.3408          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.495 |
| 0.3421        | 0.9667 | 290  | 0.3404          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.495 |
| 0.2935        | 1.0    | 300  | 0.3399          | 0.981    | 0.9810    | 0.981  | 0.9810 | 0.495 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1