Downloads · 30 days
9
0% of all-time downloads
oussama/layoutlmv3-finetuned-invoice
layoutlmv3-finetuned-invoice is a token classification model from oussama. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
9
0% of all-time downloads
All-time downloads
2.1K
Public
Parameters
126M
5.5 GB on disk
Likes
6
Public
Click a slice to open those files.
.bin504 MB · 50%
How the weights are stored.
F32126M · 100%
From the Hugging Face model README
This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.0 | 100 | 0.0967 | 0.958 | 0.9716 | 0.9648 | 0.9956 |
| No log | 4.0 | 200 | 0.0222 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 6.0 | 300 | 0.0171 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 8.0 | 400 | 0.0136 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1307 | 10.0 | 500 | 0.0117 | 0.964 | 0.9777 | 0.9708 | 0.9962 |
| 0.1307 | 12.0 | 600 | 0.0099 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1307 | 14.0 | 700 | 0.0094 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1307 | 16.0 | 800 | 0.0071 | 0.9918 | 0.9838 | 0.9878 | 0.9983 |
| 0.1307 | 18.0 | 900 | 0.0026 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
| 0.0089 | 20.0 | 1000 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0089 | 22.0 | 1100 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0089 | 24.0 | 1200 | 0.0015 | 1.0 | 0.9980 | 0.9990 | 0.9998 |
| 0.0089 | 26.0 | 1300 | 0.0015 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
| 0.0089 | 28.0 | 1400 | 0.0014 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
| 0.0025 | 30.0 | 1500 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 32.0 | 1600 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 34.0 | 1700 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 36.0 | 1800 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 38.0 | 1900 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0019 | 40.0 | 2000 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |