File size: 3,239 Bytes
0bbc6fb c89b838 0bbc6fb c89b838 0bbc6fb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv1-er-ner
results: []
---
<!-- 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. -->
# layoutlmv1-er-ner
This model is a fine-tuned version of [renjithks/layoutlmv1-cord-ner](https://huggingface.co/renjithks/layoutlmv1-cord-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2092
- Precision: 0.7202
- Recall: 0.7238
- F1: 0.7220
- Accuracy: 0.9639
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 41 | 0.2444 | 0.4045 | 0.3996 | 0.4020 | 0.9226 |
| No log | 2.0 | 82 | 0.1640 | 0.5319 | 0.6098 | 0.5682 | 0.9455 |
| No log | 3.0 | 123 | 0.1531 | 0.6324 | 0.6614 | 0.6466 | 0.9578 |
| No log | 4.0 | 164 | 0.1440 | 0.6927 | 0.6743 | 0.6834 | 0.9620 |
| No log | 5.0 | 205 | 0.1520 | 0.6750 | 0.6958 | 0.6853 | 0.9613 |
| No log | 6.0 | 246 | 0.1597 | 0.6840 | 0.6987 | 0.6913 | 0.9605 |
| No log | 7.0 | 287 | 0.1910 | 0.7002 | 0.6887 | 0.6944 | 0.9605 |
| No log | 8.0 | 328 | 0.1860 | 0.6834 | 0.6923 | 0.6878 | 0.9609 |
| No log | 9.0 | 369 | 0.1665 | 0.6785 | 0.7102 | 0.6940 | 0.9624 |
| No log | 10.0 | 410 | 0.1816 | 0.7016 | 0.7052 | 0.7034 | 0.9624 |
| No log | 11.0 | 451 | 0.1808 | 0.6913 | 0.7166 | 0.7038 | 0.9638 |
| No log | 12.0 | 492 | 0.2165 | 0.712 | 0.7023 | 0.7071 | 0.9628 |
| 0.1014 | 13.0 | 533 | 0.2135 | 0.6979 | 0.7109 | 0.7043 | 0.9613 |
| 0.1014 | 14.0 | 574 | 0.2154 | 0.6906 | 0.7109 | 0.7006 | 0.9612 |
| 0.1014 | 15.0 | 615 | 0.2118 | 0.6902 | 0.7016 | 0.6958 | 0.9615 |
| 0.1014 | 16.0 | 656 | 0.2091 | 0.6985 | 0.7080 | 0.7032 | 0.9623 |
| 0.1014 | 17.0 | 697 | 0.2104 | 0.7118 | 0.7123 | 0.7121 | 0.9630 |
| 0.1014 | 18.0 | 738 | 0.2081 | 0.7129 | 0.7231 | 0.7179 | 0.9638 |
| 0.1014 | 19.0 | 779 | 0.2093 | 0.7205 | 0.7231 | 0.7218 | 0.9638 |
| 0.1014 | 20.0 | 820 | 0.2092 | 0.7202 | 0.7238 | 0.7220 | 0.9639 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
|