metadata
library_name: transformers
base_model: 5CD-AI/Vietnamese-Sentiment-visobert
tags:
- text2text-classification
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: tuning-sentiment-5cdviso-v2
results: []
tuning-sentiment-5cdviso-v2
This model is a fine-tuned version of 5CD-AI/Vietnamese-Sentiment-visobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5569
- Accuracy: 0.9076
- F1: 0.9077
- Precision: 0.9080
- Recall: 0.9076
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2969 | 1.0776 | 500 | 0.3242 | 0.8963 | 0.8969 | 0.8984 | 0.8963 |
| 0.1866 | 2.1552 | 1000 | 0.5569 | 0.9076 | 0.9077 | 0.9080 | 0.9076 |
| 0.2202 | 3.2328 | 1500 | 1.0544 | 0.9067 | 0.9069 | 0.9080 | 0.9067 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0