Downloads · 30 days
6
6% of all-time downloads
layoutlmv3-finetuned-trf1-v2
bazar-tech/layoutlmv3-finetuned-trf1-v2
layoutlmv3-finetuned-trf1-v2 is a token classification model from bazar-tech. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
98
Public
Parameters
126M
9.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors504 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- layoutlmv3
- Access
- Public
- Created
- Jan 7, 2026
- Updated
- Jan 7, 2026
- SHA
- f50afa67
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. -->
layoutlmv3-finetuned-trf1-v2
This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0871
- F1: 0.8814
- Precision: 0.8966
- Recall: 0.8667
- Accuracy: 0.9882
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: 2
- eval_batch_size: 2
- 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
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0606 | 15.625 | 250 | 0.1710 | 0.7069 | 0.7321 | 0.6833 | 0.9647 |
| 0.0082 | 31.25 | 500 | 0.2174 | 0.8525 | 0.8387 | 0.8667 | 0.9681 |
| 0.0035 | 46.875 | 750 | 0.0848 | 0.8667 | 0.8667 | 0.8667 | 0.9882 |
| 0.0023 | 62.5 | 1000 | 0.0883 | 0.8667 | 0.8667 | 0.8667 | 0.9874 |
| 0.0017 | 78.125 | 1250 | 0.0860 | 0.8739 | 0.8814 | 0.8667 | 0.9874 |
| 0.0014 | 93.75 | 1500 | 0.0904 | 0.8739 | 0.8814 | 0.8667 | 0.9866 |
| 0.0012 | 109.375 | 1750 | 0.0883 | 0.8739 | 0.8814 | 0.8667 | 0.9874 |
| 0.001 | 125.0 | 2000 | 0.0882 | 0.8739 | 0.8814 | 0.8667 | 0.9874 |
| 0.0009 | 140.625 | 2250 | 0.0865 | 0.8814 | 0.8966 | 0.8667 | 0.9882 |
| 0.0009 | 156.25 | 2500 | 0.0871 | 0.8814 | 0.8966 | 0.8667 | 0.9882 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Jan 7, 2026
- Updated
- Jan 7, 2026