Downloads · 30 days
0
Revision_11_03_PhoBert_Lexical_Meta_Q1-52K
RonTon05/Revision_11_03_PhoBert_Lexical_Meta_Q1-52K
Revision_11_03_PhoBert_Lexical_Meta_Q1-52K is a machine learning model from RonTon05. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as agpl-3.0.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Mar 11, 2026
Parameters
270M
2.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.1 GB · 100%
At a glance
- Library
- transformers
- License
- agpl-3.0
- Access
- Public
- Created
- Mar 11, 2026
- Updated
- Mar 11, 2026
- SHA
- dfeb7b90
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. -->
Revision_11_03_PhoBert_Lexical_Meta_Q1-52K
This model is a fine-tuned version of phunganhsang/Revision_PhoBert_Lexical_Dataset_52k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8133
- Accuracy: 0.6855
- F1: 0.6854
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0.4065 | 100 | 1.1455 | 0.6914 | 0.6913 |
| No log | 0.8130 | 200 | 0.9088 | 0.7134 | 0.7132 |
| 0.2453 | 1.2195 | 300 | 1.1464 | 0.7492 | 0.7485 |
| 0.2453 | 1.6260 | 400 | 0.9775 | 0.7466 | 0.7459 |
| 0.1333 | 2.0325 | 500 | 1.5463 | 0.6851 | 0.6850 |
| 0.1333 | 2.4390 | 600 | 1.6661 | 0.6744 | 0.6742 |
| 0.1333 | 2.8455 | 700 | 1.3922 | 0.7099 | 0.7099 |
| 0.0813 | 3.2520 | 800 | 1.7493 | 0.6641 | 0.6637 |
| 0.0813 | 3.6585 | 900 | 1.5182 | 0.7181 | 0.7179 |
| 0.0476 | 4.0650 | 1000 | 1.8127 | 0.6856 | 0.6855 |
| 0.0476 | 4.4715 | 1100 | 1.7224 | 0.7011 | 0.7011 |
| 0.0476 | 4.8780 | 1200 | 1.8133 | 0.6855 | 0.6854 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- License
- agpl-3.0
- Created
- Mar 11, 2026
- Updated
- Mar 11, 2026