---
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: 2504v2
  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. -->

# 2504v2

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: 0.6769
- Accuracy: 0.8655
- Precision: 0.8660
- Recall: 0.8655
- F1: 0.8655
- Ratio: 0.5168

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- 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: 10
- label_smoothing_factor: 0.2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 4.1824        | 0.3896 | 10   | 2.4179          | 0.5084   | 0.3727    | 0.3389 | 0.3212 | 0.7479 |
| 1.997         | 0.7792 | 20   | 1.6877          | 0.5462   | 0.5489    | 0.5462 | 0.5398 | 0.3824 |
| 1.4096        | 1.1688 | 30   | 1.2832          | 0.5924   | 0.5939    | 0.5924 | 0.5908 | 0.5630 |
| 1.1296        | 1.5584 | 40   | 1.1040          | 0.6176   | 0.6187    | 0.6176 | 0.6168 | 0.5462 |
| 1.0408        | 1.9481 | 50   | 0.9666          | 0.7227   | 0.7292    | 0.7227 | 0.7207 | 0.5840 |
| 0.9242        | 2.3377 | 60   | 0.8829          | 0.7815   | 0.7816    | 0.7815 | 0.7815 | 0.4916 |
| 0.8948        | 2.7273 | 70   | 0.8146          | 0.7899   | 0.7940    | 0.7899 | 0.7892 | 0.4412 |
| 0.842         | 3.1169 | 80   | 0.7745          | 0.7941   | 0.8101    | 0.7941 | 0.7914 | 0.6134 |
| 0.7715        | 3.5065 | 90   | 0.7244          | 0.8277   | 0.8279    | 0.8277 | 0.8277 | 0.4874 |
| 0.7361        | 3.8961 | 100  | 0.7224          | 0.8151   | 0.8243    | 0.8151 | 0.8138 | 0.5840 |
| 0.7115        | 4.2857 | 110  | 0.7004          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.7076        | 4.6753 | 120  | 0.6940          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.4832 |
| 0.7026        | 5.0649 | 130  | 0.6936          | 0.8487   | 0.8491    | 0.8487 | 0.8487 | 0.5168 |
| 0.6717        | 5.4545 | 140  | 0.6912          | 0.8571   | 0.8581    | 0.8571 | 0.8571 | 0.4748 |
| 0.7166        | 5.8442 | 150  | 0.6867          | 0.8571   | 0.8575    | 0.8571 | 0.8571 | 0.5168 |
| 0.6606        | 6.2338 | 160  | 0.6812          | 0.8613   | 0.8616    | 0.8613 | 0.8613 | 0.4874 |
| 0.6939        | 6.6234 | 170  | 0.6747          | 0.8613   | 0.8614    | 0.8613 | 0.8613 | 0.4958 |
| 0.6609        | 7.0130 | 180  | 0.6744          | 0.8613   | 0.8616    | 0.8613 | 0.8613 | 0.5126 |
| 0.6388        | 7.4026 | 190  | 0.6790          | 0.8529   | 0.8532    | 0.8529 | 0.8529 | 0.5126 |
| 0.6435        | 7.7922 | 200  | 0.6840          | 0.8571   | 0.8572    | 0.8571 | 0.8571 | 0.5084 |
| 0.6534        | 8.1818 | 210  | 0.6828          | 0.8571   | 0.8571    | 0.8571 | 0.8571 | 0.5    |
| 0.6552        | 8.5714 | 220  | 0.6818          | 0.8655   | 0.8660    | 0.8655 | 0.8655 | 0.5168 |
| 0.646         | 8.9610 | 230  | 0.6788          | 0.8655   | 0.8660    | 0.8655 | 0.8655 | 0.5168 |
| 0.6443        | 9.3506 | 240  | 0.6770          | 0.8655   | 0.8660    | 0.8655 | 0.8655 | 0.5168 |
| 0.6418        | 9.7403 | 250  | 0.6769          | 0.8655   | 0.8660    | 0.8655 | 0.8655 | 0.5168 |


### Framework versions

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