File size: 3,124 Bytes
1a70845 0153a29 1a70845 |
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 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 |
---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- mp-02/cord
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-base-cord2
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: mp-02/cord
type: mp-02/cord
metrics:
- name: Precision
type: precision
value: 0.9466882067851373
- name: Recall
type: recall
value: 0.9614438063986874
- name: F1
type: f1
value: 0.9540089540089539
- name: Accuracy
type: accuracy
value: 0.9611161939615737
---
<!-- 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-base-cord2
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the mp-02/cord dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1856
- Precision: 0.9467
- Recall: 0.9614
- F1: 0.9540
- Accuracy: 0.9611
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 3000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 100 | 1.2612 | 0.6788 | 0.7629 | 0.7184 | 0.7685 |
| No log | 2.0 | 200 | 0.5621 | 0.8674 | 0.8802 | 0.8738 | 0.8916 |
| No log | 3.0 | 300 | 0.3639 | 0.8846 | 0.9114 | 0.8978 | 0.9186 |
| No log | 4.0 | 400 | 0.3197 | 0.9153 | 0.9393 | 0.9271 | 0.9410 |
| 0.8719 | 5.0 | 500 | 0.2304 | 0.9357 | 0.9549 | 0.9452 | 0.9543 |
| 0.8719 | 6.0 | 600 | 0.2069 | 0.9389 | 0.9573 | 0.9480 | 0.9556 |
| 0.8719 | 7.0 | 700 | 0.2081 | 0.9459 | 0.9606 | 0.9532 | 0.9593 |
| 0.8719 | 8.0 | 800 | 0.1901 | 0.9532 | 0.9688 | 0.9609 | 0.9666 |
| 0.8719 | 9.0 | 900 | 0.1559 | 0.9515 | 0.9647 | 0.9580 | 0.9671 |
| 0.136 | 10.0 | 1000 | 0.1856 | 0.9467 | 0.9614 | 0.9540 | 0.9611 |
| 0.136 | 11.0 | 1100 | 0.2020 | 0.9537 | 0.9631 | 0.9584 | 0.9629 |
| 0.136 | 12.0 | 1200 | 0.1908 | 0.9552 | 0.9631 | 0.9592 | 0.9620 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
|