---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: modelofinenew
  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. -->

# modelofinenew

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: 2.2185
- Accuracy: 0.5126
- F1: 0.5338

## 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: 20
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 1.9546        | 1.6129  | 50   | 2.5028          | 0.2101   | 0.2019 |
| 1.7901        | 3.2258  | 100  | 2.6787          | 0.1849   | 0.1805 |
| 1.6177        | 4.8387  | 150  | 2.3416          | 0.3445   | 0.3332 |
| 1.2977        | 6.4516  | 200  | 2.0729          | 0.4202   | 0.4060 |
| 0.9411        | 8.0645  | 250  | 1.9746          | 0.4706   | 0.4583 |
| 0.595         | 9.6774  | 300  | 1.8840          | 0.5126   | 0.5167 |
| 0.3374        | 11.2903 | 350  | 1.8955          | 0.4958   | 0.4977 |
| 0.1974        | 12.9032 | 400  | 1.9658          | 0.5378   | 0.5169 |
| 0.0981        | 14.5161 | 450  | 2.2185          | 0.5126   | 0.5338 |
| 0.05          | 16.1290 | 500  | 2.3554          | 0.5042   | 0.5096 |
| 0.0312        | 17.7419 | 550  | 2.4366          | 0.5294   | 0.5289 |
| 0.0235        | 19.3548 | 600  | 2.5235          | 0.5210   | 0.5181 |
| 0.0194        | 20.9677 | 650  | 2.5713          | 0.5294   | 0.5289 |
| 0.0166        | 22.5806 | 700  | 2.6188          | 0.5294   | 0.5289 |
| 0.0148        | 24.1935 | 750  | 2.6473          | 0.5294   | 0.5289 |
| 0.0136        | 25.8065 | 800  | 2.6742          | 0.5210   | 0.5218 |
| 0.013         | 27.4194 | 850  | 2.6920          | 0.5210   | 0.5218 |
| 0.0129        | 29.0323 | 900  | 2.6961          | 0.5210   | 0.5218 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1