metadata
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: checkpoint
results: []
checkpoint
This model is a fine-tuned version of vinai/phobert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1674
- Accuracy: 0.4286
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 1.3602 | 0.5714 |
| No log | 2.0 | 14 | 1.3269 | 0.5714 |
| No log | 3.0 | 21 | 1.2438 | 0.2857 |
| No log | 4.0 | 28 | 1.1971 | 0.4286 |
| No log | 5.0 | 35 | 1.2036 | 0.2857 |
| No log | 6.0 | 42 | 1.1996 | 0.2857 |
| No log | 7.0 | 49 | 1.1651 | 0.4286 |
| No log | 8.0 | 56 | 1.1406 | 0.4286 |
| No log | 9.0 | 63 | 1.1620 | 0.4286 |
| No log | 10.0 | 70 | 1.1674 | 0.4286 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3