Downloads · 30 days
6
13% of all-time downloads
phobert-human-tl-seed-24
trhgquan/phobert-human-tl-seed-24
phobert-human-tl-seed-24 is a text classification model from trhgquan. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
45
Public
Parameters
135M
9.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors540 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jul 8, 2025
- Updated
- Jul 8, 2025
- SHA
- 8b240032
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
phobert-human-tl-seed-24
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: 0.4536
- 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 | 0.5144 | 0.8237 | 0.5296 | 0.3491 | 0.3313 |
| 0.5988 | 2.0 | 692 | 0.4708 | 0.8305 | 0.6087 | 0.4030 | 0.4154 |
| 0.4669 | 3.0 | 1038 | 0.4640 | 0.8316 | 0.6565 | 0.4041 | 0.4188 |
| 0.4669 | 4.0 | 1384 | 0.4664 | 0.8376 | 0.7006 | 0.4177 | 0.4389 |
| 0.4619 | 5.0 | 1730 | 0.4635 | 0.8365 | 0.6788 | 0.4147 | 0.4368 |
| 0.4576 | 6.0 | 2076 | 0.4599 | 0.8365 | 0.6599 | 0.4270 | 0.4462 |
| 0.4576 | 7.0 | 2422 | 0.4623 | 0.8357 | 0.6823 | 0.4133 | 0.4355 |
| 0.4552 | 8.0 | 2768 | 0.4529 | 0.8398 | 0.6587 | 0.4438 | 0.4684 |
| 0.4543 | 9.0 | 3114 | 0.4595 | 0.8342 | 0.6396 | 0.4083 | 0.4288 |
| 0.4543 | 10.0 | 3460 | 0.4604 | 0.8346 | 0.6654 | 0.4374 | 0.4541 |
| 0.4586 | 11.0 | 3806 | 0.4589 | 0.8353 | 0.6563 | 0.4105 | 0.4341 |
| 0.449 | 12.0 | 4152 | 0.4536 | 0.8391 | 0.6540 | 0.4704 | 0.4947 |
| 0.449 | 13.0 | 4498 | 0.4552 | 0.8353 | 0.6381 | 0.4202 | 0.4463 |
| 0.4579 | 14.0 | 4844 | 0.4561 | 0.8353 | 0.6440 | 0.4113 | 0.4333 |
| 0.4489 | 15.0 | 5190 | 0.4596 | 0.8338 | 0.6609 | 0.4020 | 0.4219 |
| 0.459 | 16.0 | 5536 | 0.4667 | 0.8323 | 0.6563 | 0.3975 | 0.4143 |
| 0.459 | 17.0 | 5882 | 0.4513 | 0.8379 | 0.6220 | 0.4343 | 0.4589 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 8, 2025
- Updated
- Jul 8, 2025