metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_w2v-2
results: []
PhoBERT-Final_Mixed-aug_insert_w2v-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: 1.2182
- Accuracy: 0.69
- F1: 0.6910
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 |
|---|---|---|---|---|---|
| 0.9152 | 1.0 | 86 | 0.7599 | 0.68 | 0.6556 |
| 0.6043 | 2.0 | 172 | 0.7114 | 0.7 | 0.7023 |
| 0.4061 | 3.0 | 258 | 0.7314 | 0.73 | 0.7344 |
| 0.2797 | 4.0 | 344 | 0.9199 | 0.71 | 0.7051 |
| 0.183 | 5.0 | 430 | 1.0362 | 0.71 | 0.7083 |
| 0.1371 | 6.0 | 516 | 1.1032 | 0.71 | 0.7065 |
| 0.0894 | 7.0 | 602 | 1.1811 | 0.71 | 0.7101 |
| 0.0779 | 8.0 | 688 | 1.2182 | 0.69 | 0.6910 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3