metadata
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: phobert-human-finetune-seg-seed-1337
results: []
phobert-human-finetune-seg-seed-1337
This model is a fine-tuned version of vinai/phobert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4395
- Accuracy: 0.8570
- Precision: 0.6569
- Recall: 0.6924
- F1: 0.6729
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 346 | 0.3643 | 0.8671 | 0.7013 | 0.5922 | 0.6310 |
| 0.4458 | 2.0 | 692 | 0.3549 | 0.8698 | 0.7011 | 0.6338 | 0.6625 |
| 0.2752 | 3.0 | 1038 | 0.4395 | 0.8570 | 0.6569 | 0.6924 | 0.6729 |
| 0.2752 | 4.0 | 1384 | 0.5660 | 0.8645 | 0.6781 | 0.6046 | 0.6348 |
| 0.1612 | 5.0 | 1730 | 0.6182 | 0.8230 | 0.6101 | 0.6878 | 0.6360 |
| 0.1187 | 6.0 | 2076 | 0.5680 | 0.8679 | 0.6855 | 0.6337 | 0.6545 |
| 0.1187 | 7.0 | 2422 | 0.7394 | 0.8664 | 0.6868 | 0.6266 | 0.6520 |
| 0.0864 | 8.0 | 2768 | 0.6227 | 0.8604 | 0.6723 | 0.6441 | 0.6559 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0