---
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_3
  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_3

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: 0.6181
- Accuracy: 0.8403
- Precision: 0.8404
- Recall: 0.8403
- F1: 0.8403
- Ratio: 0.5084

## 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  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.6062        | 0.1626 | 10   | 0.6718          | 0.7857   | 0.7892    | 0.7857 | 0.7851 | 0.4454 |
| 0.6043        | 0.3252 | 20   | 0.6672          | 0.8067   | 0.8075    | 0.8067 | 0.8066 | 0.5252 |
| 0.5636        | 0.4878 | 30   | 0.6729          | 0.8025   | 0.8043    | 0.8025 | 0.8022 | 0.4622 |
| 0.6299        | 0.6504 | 40   | 0.6506          | 0.8151   | 0.8184    | 0.8151 | 0.8147 | 0.5504 |
| 0.7213        | 0.8130 | 50   | 0.6245          | 0.8277   | 0.8278    | 0.8277 | 0.8277 | 0.4958 |
| 0.6419        | 0.9756 | 60   | 0.6181          | 0.8403   | 0.8404    | 0.8403 | 0.8403 | 0.5084 |


### Framework versions

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