metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-no-gov-8k-vnnic
results: []
metadata-cls-no-gov-8k-vnnic
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: 0.2819
- Accuracy: 0.9319
- F1: 0.7796
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5853 | 1.1364 | 150 | 0.2434 | 0.9311 | 0.7583 |
| 0.2425 | 2.2727 | 300 | 0.2510 | 0.9251 | 0.7630 |
| 0.1714 | 3.4091 | 450 | 0.2222 | 0.9345 | 0.7682 |
| 0.1274 | 4.5455 | 600 | 0.2391 | 0.9328 | 0.7862 |
| 0.1075 | 5.6818 | 750 | 0.2507 | 0.9319 | 0.7732 |
| 0.0867 | 6.8182 | 900 | 0.2808 | 0.9277 | 0.7711 |
| 0.0625 | 7.9545 | 1050 | 0.2965 | 0.9243 | 0.7674 |
| 0.0539 | 9.0909 | 1200 | 0.2819 | 0.9319 | 0.7796 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1