metadata
library_name: transformers
base_model: 5CD-AI/Vietnamese-Sentiment-visobert
tags:
- text-classification
- vietnamese
- sentiment-analysis
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: tuning-sentiment-abp-v2.2
results: []
tuning-sentiment-abp-v2.2
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: 0.9679
- Accuracy: 0.4844
- F1: 0.5232
- Precision: 0.5186
- Recall: 0.5436
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6162 | 1.0 | 607 | 0.7060 | 0.6096 | 0.5219 | 0.5977 | 0.5816 |
| 0.6188 | 2.0 | 1214 | 0.7061 | 0.6074 | 0.5241 | 0.5668 | 0.5931 |
| 0.6158 | 3.0 | 1821 | 0.7626 | 0.5935 | 0.5223 | 0.5325 | 0.5822 |
| 0.6077 | 4.0 | 2428 | 0.8325 | 0.5916 | 0.5283 | 0.5217 | 0.5974 |
| 0.5846 | 5.0 | 3035 | 0.9679 | 0.4844 | 0.5232 | 0.5186 | 0.5436 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1