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Fine-tuned_LayoutLMv3_on_SROIE-10epochs
missdua-07/Fine-tuned_LayoutLMv3_on_SROIE-10epochs
Fine-tuned_LayoutLMv3_on_SROIE-10epochs is a machine learning model from missdua-07. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- cc-by-nc-sa-4.0
- Model type
- layoutlmv3
- Access
- Public
- Created
- Aug 2, 2024
- Updated
- Aug 2, 2024
- SHA
- d67124cb
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. -->
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
Fine-tuned_LayoutLMv3_on_SROIE-10epochs
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: 0.0388
- Precision: 0.9367
- Recall: 0.9488
- F1: 0.9427
- Accuracy: 0.9953
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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0023 | 1.25 | 50 | 0.0406 | 0.9267 | 0.9467 | 0.9366 | 0.9944 |
| 0.0023 | 2.5 | 100 | 0.0417 | 0.9190 | 0.9481 | 0.9333 | 0.9938 |
| 0.0024 | 3.75 | 150 | 0.0374 | 0.9263 | 0.9503 | 0.9381 | 0.9948 |
| 0.0012 | 5.0 | 200 | 0.0363 | 0.9381 | 0.9496 | 0.9438 | 0.9953 |
| 0.001 | 6.25 | 250 | 0.0393 | 0.9330 | 0.9431 | 0.9380 | 0.9951 |
| 0.0008 | 7.5 | 300 | 0.0387 | 0.9368 | 0.9503 | 0.9435 | 0.9953 |
| 0.0006 | 8.75 | 350 | 0.0387 | 0.9367 | 0.9488 | 0.9427 | 0.9953 |
| 0.0005 | 10.0 | 400 | 0.0388 | 0.9367 | 0.9488 | 0.9427 | 0.9953 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Aug 2, 2024
- Updated
- Aug 2, 2024