---
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: 2404v5
  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. -->

# 2404v5

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: 0.6586
- Accuracy: 0.8403
- Precision: 0.8407
- Recall: 0.8403
- F1: 0.8403
- 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: 5e-05
- train_batch_size: 10
- eval_batch_size: 2
- seed: 42
- 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: 4
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 3.0551        | 0.1626 | 10   | 1.7145          | 0.5      | 0.5       | 0.5    | 0.3733 | 0.0504 |
| 1.0346        | 0.3252 | 20   | 0.8860          | 0.5336   | 0.5558    | 0.5336 | 0.4822 | 0.8151 |
| 0.8531        | 0.4878 | 30   | 0.8174          | 0.5672   | 0.6156    | 0.5672 | 0.5166 | 0.1765 |
| 0.8279        | 0.6504 | 40   | 0.7147          | 0.7563   | 0.7928    | 0.7563 | 0.7485 | 0.6765 |
| 0.744         | 0.8130 | 50   | 0.6403          | 0.8067   | 0.8099    | 0.8067 | 0.8062 | 0.5504 |
| 0.6594        | 0.9756 | 60   | 0.6299          | 0.7983   | 0.8004    | 0.7983 | 0.7980 | 0.5420 |
| 0.5973        | 1.1382 | 70   | 0.6320          | 0.8193   | 0.8204    | 0.8193 | 0.8192 | 0.5294 |
| 0.5934        | 1.3008 | 80   | 0.6306          | 0.8151   | 0.8184    | 0.8151 | 0.8147 | 0.4496 |
| 0.5529        | 1.4634 | 90   | 0.6442          | 0.8193   | 0.8195    | 0.8193 | 0.8193 | 0.5126 |
| 0.5618        | 1.6260 | 100  | 0.6186          | 0.8193   | 0.8204    | 0.8193 | 0.8192 | 0.5294 |
| 0.5632        | 1.7886 | 110  | 0.5845          | 0.8361   | 0.8373    | 0.8361 | 0.8360 | 0.5294 |
| 0.5886        | 1.9512 | 120  | 0.5752          | 0.8361   | 0.8367    | 0.8361 | 0.8361 | 0.5210 |
| 0.5596        | 2.1138 | 130  | 0.5760          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.4964        | 2.2764 | 140  | 0.6181          | 0.8361   | 0.8367    | 0.8361 | 0.8361 | 0.4790 |
| 0.5014        | 2.4390 | 150  | 0.6422          | 0.8361   | 0.8381    | 0.8361 | 0.8359 | 0.5378 |
| 0.5251        | 2.6016 | 160  | 0.6033          | 0.8403   | 0.8428    | 0.8403 | 0.8401 | 0.5420 |
| 0.4723        | 2.7642 | 170  | 0.5839          | 0.8487   | 0.8503    | 0.8487 | 0.8486 | 0.5336 |
| 0.4864        | 2.9268 | 180  | 0.5837          | 0.8613   | 0.8616    | 0.8613 | 0.8613 | 0.5126 |
| 0.4512        | 3.0894 | 190  | 0.5973          | 0.8487   | 0.8491    | 0.8487 | 0.8487 | 0.5168 |
| 0.477         | 3.2520 | 200  | 0.6159          | 0.8403   | 0.8404    | 0.8403 | 0.8403 | 0.5084 |
| 0.4198        | 3.4146 | 210  | 0.6523          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.4322        | 3.5772 | 220  | 0.6646          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.4889        | 3.7398 | 230  | 0.6632          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |
| 0.4409        | 3.9024 | 240  | 0.6589          | 0.8403   | 0.8407    | 0.8403 | 0.8403 | 0.5168 |


### Framework versions

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