Hugging Face's logo

trhgquan
/
phobert-human-tl-seed-42

Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Model card Files Metrics Community
phobert-human-tl-seed-42 / README.md
trhgquan's picture
trhgquan
End of training
681fe98 verified
preview code
|
raw
history blame contribute delete
3.15 kB
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-tl-seed-42
    results: []

phobert-human-tl-seed-42

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: 0.4535
  • Accuracy: 0.8391
  • Precision: 0.6540
  • Recall: 0.4704
  • F1: 0.4947

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 0.5155 0.8230 0.5189 0.3466 0.3267
0.5915 2.0 692 0.4712 0.8305 0.6068 0.4030 0.4152
0.4672 3.0 1038 0.4644 0.8327 0.6736 0.4060 0.4224
0.4672 4.0 1384 0.4667 0.8361 0.6805 0.4135 0.4321
0.4614 5.0 1730 0.4633 0.8361 0.6715 0.4145 0.4368
0.4576 6.0 2076 0.4599 0.8357 0.6605 0.4245 0.4437
0.4576 7.0 2422 0.4622 0.8365 0.6768 0.4147 0.4375
0.4553 8.0 2768 0.4527 0.8383 0.6430 0.4410 0.4643
0.4542 9.0 3114 0.4601 0.8335 0.6428 0.4059 0.4254
0.4542 10.0 3460 0.4600 0.8342 0.6642 0.4372 0.4537
0.4588 11.0 3806 0.4585 0.8353 0.6504 0.4105 0.4342
0.4487 12.0 4152 0.4535 0.8391 0.6540 0.4704 0.4947
0.4487 13.0 4498 0.4552 0.8361 0.6410 0.4205 0.4471
0.4577 14.0 4844 0.4558 0.8353 0.6467 0.4113 0.4336
0.4487 15.0 5190 0.4589 0.8335 0.6571 0.4019 0.4216
0.4586 16.0 5536 0.4665 0.8327 0.6580 0.3987 0.4161
0.4586 17.0 5882 0.4513 0.8379 0.6188 0.4343 0.4590

Framework versions

  • Transformers 4.51.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.0