metadata
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: my_model
results: []
model_without_stopwords
This model is a fine-tuned version of vinai/phobert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3275
- F1: 0.7678
- Precision: 0.7851
- Recall: 0.7512
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.1919 | 1.0 | 2423 | 0.3585 | 0.7545 | 0.7644 | 0.7448 |
| 0.2079 | 2.0 | 4846 | 0.3275 | 0.7678 | 0.7851 | 0.7512 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3