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layoutlmv3-finetuned-invoice_ConControl_v3
Giannis17/layoutlmv3-finetuned-invoice_ConControl_v3
layoutlmv3-finetuned-invoice_ConControl_v3 is a token classification model from Giannis17. 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. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- layoutlmv3
- Access
- Public
- Created
- Mar 24, 2025
- Updated
- Mar 31, 2025
- SHA
- fa26ce05
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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-invoice_ConControl_v3
This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3493
- Precision: 0.0049
- Recall: 0.0587
- F1: 0.0090
- Accuracy: 0.0569
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 2 | 2.6128 | 0.0036 | 0.0475 | 0.0067 | 0.0087 |
| No log | 2.0 | 4 | 2.6071 | 0.0036 | 0.0475 | 0.0067 | 0.0087 |
| No log | 3.0 | 6 | 2.5970 | 0.0034 | 0.0447 | 0.0063 | 0.0087 |
| No log | 4.0 | 8 | 2.5823 | 0.0036 | 0.0475 | 0.0067 | 0.0089 |
| No log | 5.0 | 10 | 2.5632 | 0.0041 | 0.0531 | 0.0075 | 0.0092 |
| No log | 6.0 | 12 | 2.5395 | 0.0045 | 0.0587 | 0.0084 | 0.0100 |
| No log | 7.0 | 14 | 2.5113 | 0.0045 | 0.0587 | 0.0084 | 0.0110 |
| No log | 8.0 | 16 | 2.4784 | 0.0046 | 0.0587 | 0.0085 | 0.0135 |
| No log | 9.0 | 18 | 2.4407 | 0.0044 | 0.0559 | 0.0082 | 0.0189 |
| No log | 10.0 | 20 | 2.3978 | 0.0045 | 0.0559 | 0.0083 | 0.0296 |
| No log | 11.0 | 22 | 2.3493 | 0.0049 | 0.0587 | 0.0090 | 0.0569 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu118
- Datasets 3.4.1
- Tokenizers 0.21.1
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Mar 24, 2025
- Updated
- Mar 31, 2025