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ft-ms-layoutlmv3-funsd-layoutlmv3
aisuko/ft-ms-layoutlmv3-funsd-layoutlmv3
ft-ms-layoutlmv3-funsd-layoutlmv3 is a token classification model from aisuko. 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
- Dec 14, 2023
- Updated
- Feb 29, 2024
- SHA
- b8f059fc
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Base models
Datasets
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. -->
ft-ms-layoutlmv3-funsd-layoutlmv3
This model is a fine-tuned version of microsoft/layoutlmv3-base on the aisuko/funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5755
- Precision: 0.8422
- Recall: 0.8803
- F1: 0.8608
- Accuracy: 0.8324
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 10.0 | 100 | 0.6104 | 0.8080 | 0.8614 | 0.8339 | 0.8262 |
| No log | 20.0 | 200 | 0.5755 | 0.8422 | 0.8803 | 0.8608 | 0.8324 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Dec 14, 2023
- Updated
- Feb 29, 2024