update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
metrics:
|
| 5 |
+
- precision
|
| 6 |
+
- recall
|
| 7 |
+
- f1
|
| 8 |
+
- accuracy
|
| 9 |
+
model-index:
|
| 10 |
+
- name: layoutlmv3-cord-ner
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# layoutlmv3-cord-ner
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.1215
|
| 22 |
+
- Precision: 0.9448
|
| 23 |
+
- Recall: 0.9520
|
| 24 |
+
- F1: 0.9484
|
| 25 |
+
- Accuracy: 0.9762
|
| 26 |
+
|
| 27 |
+
## Model description
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Intended uses & limitations
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training and evaluation data
|
| 36 |
+
|
| 37 |
+
More information needed
|
| 38 |
+
|
| 39 |
+
## Training procedure
|
| 40 |
+
|
| 41 |
+
### Training hyperparameters
|
| 42 |
+
|
| 43 |
+
The following hyperparameters were used during training:
|
| 44 |
+
- learning_rate: 5e-05
|
| 45 |
+
- train_batch_size: 8
|
| 46 |
+
- eval_batch_size: 8
|
| 47 |
+
- seed: 42
|
| 48 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 49 |
+
- lr_scheduler_type: linear
|
| 50 |
+
- num_epochs: 10
|
| 51 |
+
|
| 52 |
+
### Training results
|
| 53 |
+
|
| 54 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 55 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 56 |
+
| No log | 1.0 | 113 | 0.1771 | 0.8485 | 0.8925 | 0.8700 | 0.9393 |
|
| 57 |
+
| No log | 2.0 | 226 | 0.1584 | 0.8915 | 0.9146 | 0.9029 | 0.9524 |
|
| 58 |
+
| No log | 3.0 | 339 | 0.1153 | 0.9160 | 0.9309 | 0.9234 | 0.9686 |
|
| 59 |
+
| No log | 4.0 | 452 | 0.1477 | 0.9110 | 0.9136 | 0.9123 | 0.9592 |
|
| 60 |
+
| 0.1562 | 5.0 | 565 | 0.0861 | 0.9363 | 0.9443 | 0.9403 | 0.9741 |
|
| 61 |
+
| 0.1562 | 6.0 | 678 | 0.1165 | 0.9109 | 0.9415 | 0.9259 | 0.9673 |
|
| 62 |
+
| 0.1562 | 7.0 | 791 | 0.1280 | 0.9278 | 0.9367 | 0.9322 | 0.9707 |
|
| 63 |
+
| 0.1562 | 8.0 | 904 | 0.1122 | 0.9462 | 0.9453 | 0.9458 | 0.9762 |
|
| 64 |
+
| 0.0224 | 9.0 | 1017 | 0.1265 | 0.9431 | 0.9539 | 0.9485 | 0.9771 |
|
| 65 |
+
| 0.0224 | 10.0 | 1130 | 0.1215 | 0.9448 | 0.9520 | 0.9484 | 0.9762 |
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
### Framework versions
|
| 69 |
+
|
| 70 |
+
- Transformers 4.20.0.dev0
|
| 71 |
+
- Pytorch 1.11.0
|
| 72 |
+
- Datasets 2.1.0
|
| 73 |
+
- Tokenizers 0.12.1
|