metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_swap-2
results: []
PhoBERT-Final_Mixed-aug_swap-2
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2527
- Accuracy: 0.7
- F1: 0.7091
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: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8968 | 1.0 | 86 | 0.7005 | 0.68 | 0.6386 |
| 0.5324 | 2.0 | 172 | 0.6756 | 0.72 | 0.7272 |
| 0.3248 | 3.0 | 258 | 0.7112 | 0.75 | 0.7482 |
| 0.2139 | 4.0 | 344 | 0.8172 | 0.75 | 0.7545 |
| 0.1439 | 5.0 | 430 | 0.9876 | 0.7 | 0.7041 |
| 0.108 | 6.0 | 516 | 1.1343 | 0.72 | 0.7280 |
| 0.0784 | 7.0 | 602 | 1.1912 | 0.7 | 0.7091 |
| 0.0688 | 8.0 | 688 | 1.2527 | 0.7 | 0.7091 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3