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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_5
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_5
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: 0.3399
- Accuracy: 0.981
- Precision: 0.9810
- Recall: 0.981
- F1: 0.9810
- Ratio: 0.495
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----:|
| 0.3013 | 0.0333 | 10 | 0.3474 | 0.978 | 0.9783 | 0.978 | 0.9780 | 0.488 |
| 0.3087 | 0.0667 | 20 | 0.3471 | 0.979 | 0.9790 | 0.979 | 0.9790 | 0.495 |
| 0.3181 | 0.1 | 30 | 0.3527 | 0.975 | 0.9752 | 0.975 | 0.9750 | 0.489 |
| 0.3134 | 0.1333 | 40 | 0.3602 | 0.971 | 0.9714 | 0.971 | 0.9710 | 0.485 |
| 0.3002 | 0.1667 | 50 | 0.3481 | 0.979 | 0.9790 | 0.979 | 0.9790 | 0.501 |
| 0.3226 | 0.2 | 60 | 0.3547 | 0.978 | 0.9780 | 0.978 | 0.9780 | 0.496 |
| 0.2919 | 0.2333 | 70 | 0.3687 | 0.972 | 0.9724 | 0.972 | 0.9720 | 0.486 |
| 0.2932 | 0.2667 | 80 | 0.3822 | 0.965 | 0.9664 | 0.965 | 0.9650 | 0.473 |
| 0.3303 | 0.3 | 90 | 0.3754 | 0.969 | 0.9700 | 0.969 | 0.9690 | 0.477 |
| 0.3162 | 0.3333 | 100 | 0.3557 | 0.975 | 0.9750 | 0.975 | 0.9750 | 0.505 |
| 0.3012 | 0.3667 | 110 | 0.3554 | 0.974 | 0.9741 | 0.974 | 0.9740 | 0.506 |
| 0.3337 | 0.4 | 120 | 0.3629 | 0.972 | 0.9725 | 0.972 | 0.9720 | 0.484 |
| 0.3007 | 0.4333 | 130 | 0.3492 | 0.979 | 0.9792 | 0.979 | 0.9790 | 0.491 |
| 0.3283 | 0.4667 | 140 | 0.3467 | 0.979 | 0.9790 | 0.979 | 0.9790 | 0.495 |
| 0.3238 | 0.5 | 150 | 0.3410 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.497 |
| 0.3076 | 0.5333 | 160 | 0.3387 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.498 |
| 0.3348 | 0.5667 | 170 | 0.3375 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.498 |
| 0.3258 | 0.6 | 180 | 0.3401 | 0.98 | 0.9801 | 0.98 | 0.9800 | 0.494 |
| 0.3195 | 0.6333 | 190 | 0.3424 | 0.978 | 0.9781 | 0.978 | 0.9780 | 0.492 |
| 0.31 | 0.6667 | 200 | 0.3392 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.495 |
| 0.3407 | 0.7 | 210 | 0.3393 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.502 |
| 0.3494 | 0.7333 | 220 | 0.3413 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.501 |
| 0.3574 | 0.7667 | 230 | 0.3402 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.496 |
| 0.3379 | 0.8 | 240 | 0.3385 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.496 |
| 0.3532 | 0.8333 | 250 | 0.3385 | 0.982 | 0.9820 | 0.982 | 0.9820 | 0.496 |
| 0.318 | 0.8667 | 260 | 0.3425 | 0.98 | 0.9801 | 0.98 | 0.9800 | 0.494 |
| 0.3475 | 0.9 | 270 | 0.3432 | 0.98 | 0.9801 | 0.98 | 0.9800 | 0.494 |
| 0.3142 | 0.9333 | 280 | 0.3408 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.495 |
| 0.3421 | 0.9667 | 290 | 0.3404 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.495 |
| 0.2935 | 1.0 | 300 | 0.3399 | 0.981 | 0.9810 | 0.981 | 0.9810 | 0.495 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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