Downloads · 30 days
6
14% of all-time downloads
layoutlmv3-finetuned-wildreceipt
Andre002wp/layoutlmv3-finetuned-wildreceipt
layoutlmv3-finetuned-wildreceipt is a token classification model from Andre002wp. 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
44
Public
Repo size
2.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin504 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- layoutlmv3
- Access
- Public
- Created
- Sep 8, 2022
- Updated
- Sep 8, 2022
- SHA
- dc10f284
Try a prompt
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. -->
layoutlmv3-finetuned-wildreceipt
This model is a fine-tuned version of microsoft/layoutlmv3-base on the wildreceipt dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2996
- eval_precision: 0.8566
- eval_recall: 0.8614
- eval_f1: 0.8590
- eval_accuracy: 0.9178
- eval_runtime: 51.7898
- eval_samples_per_second: 9.114
- eval_steps_per_second: 2.278
- epoch: 4.97
- step: 1577
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Sep 8, 2022
- Updated
- Sep 8, 2022