File size: 2,847 Bytes
e3a9a1e 72aeaa6 e3a9a1e a6c90d4 e3a9a1e a6c90d4 e3a9a1e a6c90d4 e3a9a1e a6c90d4 e3a9a1e 72aeaa6 e3a9a1e a6c90d4 e3a9a1e a6c90d4 e3a9a1e a6c90d4 e3a9a1e |
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 |
---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- generated
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: generated
type: generated
config: sroie
split: test
args: sroie
metrics:
- name: Precision
type: precision
value: 1.0
- name: Recall
type: recall
value: 1.0
- name: F1
type: f1
value: 1.0
- name: Accuracy
type: accuracy
value: 1.0
---
<!-- 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-invoice
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0041
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 2.0 | 100 | 0.0910 | 0.9 | 0.9128 | 0.9063 | 0.9895 |
| No log | 4.0 | 200 | 0.0247 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 6.0 | 300 | 0.0176 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 8.0 | 400 | 0.0156 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1327 | 10.0 | 500 | 0.0143 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1327 | 12.0 | 600 | 0.0130 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1327 | 14.0 | 700 | 0.0112 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1327 | 16.0 | 800 | 0.0093 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1327 | 18.0 | 900 | 0.0047 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
| 0.0113 | 20.0 | 1000 | 0.0041 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
|