metadata
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: project-2
results: []
project-2
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: 0.4960
- Accuracy: 0.8288
- F1: 0.8286
- Precision: 0.8303
- Recall: 0.8288
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.5283 | 1.0 | 1407 | 0.4587 | 0.7804 | 0.7789 | 0.7883 | 0.7804 |
| 0.4276 | 2.0 | 2814 | 0.4844 | 0.7708 | 0.7649 | 0.8012 | 0.7708 |
| 0.3729 | 3.0 | 4221 | 0.4045 | 0.8216 | 0.8214 | 0.8232 | 0.8216 |
| 0.314 | 4.0 | 5628 | 0.5072 | 0.8116 | 0.8098 | 0.8236 | 0.8116 |
| 0.268 | 5.0 | 7035 | 0.5467 | 0.8036 | 0.8008 | 0.8215 | 0.8036 |
| 0.2162 | 6.0 | 8442 | 0.4960 | 0.8288 | 0.8286 | 0.8303 | 0.8288 |
| 0.1786 | 7.0 | 9849 | 0.5648 | 0.828 | 0.8280 | 0.8280 | 0.828 |
| 0.1514 | 8.0 | 11256 | 0.6146 | 0.8232 | 0.8231 | 0.8240 | 0.8232 |
| 0.127 | 9.0 | 12663 | 0.6901 | 0.8272 | 0.8270 | 0.8284 | 0.8272 |
| 0.1041 | 10.0 | 14070 | 0.7387 | 0.8256 | 0.8253 | 0.8276 | 0.8256 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0