---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fm-tc-authentic
  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. -->

# fm-tc-authentic

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2183
- Accuracy: 0.684
- Precision: 0.4290
- Recall: 0.4443
- F1: 0.4224

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2298        | 1.0   | 568  | 1.5513          | 0.576    | 0.2101    | 0.2781 | 0.2186 |
| 1.4142        | 2.0   | 1136 | 1.2728          | 0.652    | 0.3275    | 0.3903 | 0.3517 |
| 1.1276        | 3.0   | 1704 | 1.2183          | 0.684    | 0.4290    | 0.4443 | 0.4224 |
| 0.8384        | 4.0   | 2272 | 1.2388          | 0.672    | 0.5085    | 0.4718 | 0.4609 |
| 0.6867        | 5.0   | 2840 | 1.2870          | 0.674    | 0.5075    | 0.4686 | 0.4597 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1