metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_w2v-1
results: []
PhoBERT-Final_Mixed-aug_insert_w2v-1
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: 1.0909
- Accuracy: 0.76
- F1: 0.7596
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: 41
- 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 |
|---|---|---|---|---|---|
| 0.9106 | 1.0 | 86 | 0.7115 | 0.73 | 0.7319 |
| 0.5874 | 2.0 | 172 | 0.6895 | 0.71 | 0.7119 |
| 0.4037 | 3.0 | 258 | 0.8004 | 0.69 | 0.6842 |
| 0.2653 | 4.0 | 344 | 0.7982 | 0.72 | 0.7264 |
| 0.1761 | 5.0 | 430 | 0.9948 | 0.76 | 0.7608 |
| 0.1044 | 6.0 | 516 | 1.0613 | 0.75 | 0.7518 |
| 0.0844 | 7.0 | 602 | 1.0984 | 0.75 | 0.7478 |
| 0.0604 | 8.0 | 688 | 1.0909 | 0.76 | 0.7596 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3