metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-no-gov
results: []
metadata-cls-no-gov
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3806
- Accuracy: 0.9303
- F1: 0.8372
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5915 | 1.9608 | 200 | 0.2063 | 0.9406 | 0.7585 |
| 0.1888 | 3.9216 | 400 | 0.1895 | 0.9426 | 0.8653 |
| 0.1081 | 5.8824 | 600 | 0.2354 | 0.9344 | 0.8188 |
| 0.0761 | 7.8431 | 800 | 0.2972 | 0.9324 | 0.8176 |
| 0.0483 | 9.8039 | 1000 | 0.2985 | 0.9324 | 0.8385 |
| 0.0348 | 11.7647 | 1200 | 0.3409 | 0.9283 | 0.8521 |
| 0.0271 | 13.7255 | 1400 | 0.3593 | 0.9283 | 0.8211 |
| 0.019 | 15.6863 | 1600 | 0.3608 | 0.9324 | 0.8352 |
| 0.0136 | 17.6471 | 1800 | 0.3729 | 0.9324 | 0.8358 |
| 0.0095 | 19.6078 | 2000 | 0.3806 | 0.9303 | 0.8372 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1