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---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: FS_25_05
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. -->
# FS_25_05
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: 0.1403
- Accuracy: 0.9745
- Precision: 0.9751
- Recall: 0.9743
- F1: 0.9744
- Ratio: 0.0529
## 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 | Ratio |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 1.7313 | 1.0 | 362 | 1.5891 | 0.9137 | 0.9237 | 0.9138 | 0.9148 | 0.0569 |
| 0.3284 | 2.0 | 724 | 0.2812 | 0.9529 | 0.9560 | 0.9528 | 0.9533 | 0.0490 |
| 0.103 | 3.0 | 1086 | 0.1580 | 0.9667 | 0.9681 | 0.9665 | 0.9663 | 0.0510 |
| 0.1073 | 4.0 | 1448 | 0.1532 | 0.9686 | 0.9693 | 0.9685 | 0.9686 | 0.0529 |
| 0.1295 | 5.0 | 1810 | 0.1403 | 0.9745 | 0.9751 | 0.9743 | 0.9744 | 0.0529 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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