metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentiment_phobert
results: []
sentiment_phobert
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: 0.4195
- Accuracy: 0.8330
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.406 | 1.0 | 2958 | 0.4195 | 0.8330 |
| 0.3451 | 2.0 | 5916 | 0.4343 | 0.8351 |
| 0.2871 | 3.0 | 8874 | 0.4593 | 0.8393 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3