---
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: 2404v6
  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. -->

# 2404v6

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: 0.5939
- Accuracy: 0.8445
- Precision: 0.8451
- Recall: 0.8445
- F1: 0.8445
- Ratio: 0.4790

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 2
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.5731        | 0.2597 | 10   | 0.5646          | 0.8613   | 0.8645    | 0.8613 | 0.8610 | 0.4538 |
| 0.5515        | 0.5195 | 20   | 0.5569          | 0.8613   | 0.8626    | 0.8613 | 0.8612 | 0.4706 |
| 0.5164        | 0.7792 | 30   | 0.6079          | 0.8277   | 0.8363    | 0.8277 | 0.8266 | 0.5798 |
| 0.5641        | 1.0390 | 40   | 0.5728          | 0.8571   | 0.8608    | 0.8571 | 0.8568 | 0.4496 |
| 0.4665        | 1.2987 | 50   | 0.5992          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.4632        | 1.5584 | 60   | 0.5990          | 0.8613   | 0.8634    | 0.8613 | 0.8611 | 0.4622 |
| 0.4456        | 1.8182 | 70   | 0.5939          | 0.8445   | 0.8451    | 0.8445 | 0.8445 | 0.4790 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1