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---
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
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