metadata
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: UIT-VSFC-PhoBert-CLSModel-v1
results: []
UIT-VSFC-PhoBert-CLSModel-v1
This model is a fine-tuned version of vinai/phobert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2107
- Accuracy: 0.9400
- F1: 0.8137
- Precision: 0.8659
- Recall: 0.7848
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: 128
- eval_batch_size: 128
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 90 | 0.3109 | 0.9154 | 0.6245 | 0.6099 | 0.6398 |
| No log | 2.0 | 180 | 0.2242 | 0.9337 | 0.7738 | 0.8546 | 0.7438 |
| No log | 3.0 | 270 | 0.2107 | 0.9400 | 0.8137 | 0.8659 | 0.7848 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1