Downloads · 30 days
5
9% of all-time downloads
layoutlmv3-finetuned-cord_100
Uddarajuvarma/layoutlmv3-finetuned-cord_100
layoutlmv3-finetuned-cord_100 is a token classification model from Uddarajuvarma. 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
57
Public
Parameters
126M
5 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
- Jun 13, 2024
- Updated
- Jun 13, 2024
- SHA
- cc8b842f
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-cord_100
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: 0.1994
- Precision: 0.9444
- Recall: 0.9552
- F1: 0.9498
- Accuracy: 0.9606
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.0833 | 250 | 0.6541 | 0.8122 | 0.8116 | 0.8119 | 0.8439 |
| 0.9666 | 4.1667 | 500 | 0.3834 | 0.8660 | 0.8739 | 0.8699 | 0.9029 |
| 0.9666 | 6.25 | 750 | 0.2589 | 0.9136 | 0.9240 | 0.9188 | 0.9398 |
| 0.2307 | 8.3333 | 1000 | 0.2444 | 0.9246 | 0.9316 | 0.9281 | 0.9470 |
| 0.2307 | 10.4167 | 1250 | 0.2125 | 0.9311 | 0.9445 | 0.9378 | 0.9508 |
| 0.1035 | 12.5 | 1500 | 0.1878 | 0.9301 | 0.9498 | 0.9398 | 0.9572 |
| 0.1035 | 14.5833 | 1750 | 0.2201 | 0.9240 | 0.9422 | 0.9330 | 0.9521 |
| 0.0557 | 16.6667 | 2000 | 0.1962 | 0.9393 | 0.9529 | 0.9461 | 0.9601 |
| 0.0557 | 18.75 | 2250 | 0.1945 | 0.9452 | 0.9567 | 0.9509 | 0.9627 |
| 0.0388 | 20.8333 | 2500 | 0.1994 | 0.9444 | 0.9552 | 0.9498 | 0.9606 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- License
- cc-by-nc-sa-4.0
- Created
- Jun 13, 2024
- Updated
- Jun 13, 2024