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---
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: 080524_epoch_3
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. -->
# 080524_epoch_3
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: 0.7190
- Accuracy: 0.8151
- Precision: 0.8431
- Recall: 0.8151
- F1: 0.8113
- Ratio: 0.6429
## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 2
- seed: 47
- 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: 1
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.4532 | 0.1176 | 10 | 0.6742 | 0.8193 | 0.8367 | 0.8193 | 0.8170 | 0.6134 |
| 0.4299 | 0.2353 | 20 | 0.8276 | 0.7731 | 0.8079 | 0.7731 | 0.7665 | 0.6681 |
| 0.4963 | 0.3529 | 30 | 0.7032 | 0.8235 | 0.8425 | 0.8235 | 0.8211 | 0.6176 |
| 0.3726 | 0.4706 | 40 | 0.7220 | 0.8193 | 0.8395 | 0.8193 | 0.8166 | 0.6218 |
| 0.3917 | 0.5882 | 50 | 0.8389 | 0.7941 | 0.8295 | 0.7941 | 0.7884 | 0.6639 |
| 0.4565 | 0.7059 | 60 | 0.7085 | 0.8277 | 0.8429 | 0.8277 | 0.8258 | 0.6050 |
| 0.4748 | 0.8235 | 70 | 0.6934 | 0.8109 | 0.8278 | 0.8109 | 0.8085 | 0.6134 |
| 0.4813 | 0.9412 | 80 | 0.7157 | 0.8193 | 0.8426 | 0.8193 | 0.8162 | 0.6303 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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