metadata
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Phobert_CITA_15k
results: []
Phobert_CITA_15k
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: 0.6995
- Accuracy: 0.8057
- F1: 0.8034
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4825 | 1.0 | 375 | 0.4345 | 0.8047 | 0.7947 |
| 0.3984 | 2.0 | 750 | 0.4341 | 0.8033 | 0.8030 |
| 0.3466 | 3.0 | 1125 | 0.4692 | 0.8213 | 0.8158 |
| 0.3012 | 4.0 | 1500 | 0.5128 | 0.8147 | 0.8051 |
| 0.256 | 5.0 | 1875 | 0.5427 | 0.806 | 0.8061 |
| 0.213 | 6.0 | 2250 | 0.5851 | 0.8087 | 0.8022 |
| 0.1805 | 7.0 | 2625 | 0.6466 | 0.8083 | 0.8060 |
| 0.1568 | 8.0 | 3000 | 0.6883 | 0.81 | 0.8053 |
| 0.1453 | 9.0 | 3375 | 0.6956 | 0.8083 | 0.8056 |
| 0.1467 | 10.0 | 3750 | 0.6995 | 0.8057 | 0.8034 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.21.0