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-seed-69
results: []
phobert-human-finetune-seed-69
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: 0.4456
- Accuracy: 0.8656
- Precision: 0.6916
- Recall: 0.6146
- F1: 0.6460
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 | 0.4223 | 0.8458 | 0.6342 | 0.6336 | 0.6232 |
| 0.4575 | 2.0 | 692 | 0.3914 | 0.8574 | 0.6554 | 0.5877 | 0.5935 |
| 0.2895 | 3.0 | 1038 | 0.4456 | 0.8656 | 0.6916 | 0.6146 | 0.6460 |
| 0.2895 | 4.0 | 1384 | 0.5710 | 0.8664 | 0.7133 | 0.5867 | 0.6226 |
| 0.1725 | 5.0 | 1730 | 0.6641 | 0.8585 | 0.6657 | 0.6120 | 0.6354 |
| 0.1259 | 6.0 | 2076 | 0.6784 | 0.8559 | 0.6550 | 0.6223 | 0.6356 |
| 0.1259 | 7.0 | 2422 | 0.5981 | 0.8481 | 0.6358 | 0.6313 | 0.6309 |
| 0.0902 | 8.0 | 2768 | 0.6867 | 0.8331 | 0.6259 | 0.6655 | 0.6343 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0