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# sogemi_ddt_1.0

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0375
- Precision: 0.9443
- Recall: 0.9713
- F1: 0.9576
- Accuracy: 0.9927

## 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: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.35  | 100  | 0.6022          | 0.2061    | 0.0774 | 0.1125 | 0.8634   |
| No log        | 2.7   | 200  | 0.3445          | 0.4627    | 0.3381 | 0.3907 | 0.9051   |
| No log        | 4.05  | 300  | 0.1820          | 0.7524    | 0.6619 | 0.7043 | 0.9583   |
| No log        | 5.41  | 400  | 0.1141          | 0.8742    | 0.8166 | 0.8444 | 0.9812   |
| 0.3555        | 6.76  | 500  | 0.0719          | 0.9229    | 0.9255 | 0.9242 | 0.9867   |
| 0.3555        | 8.11  | 600  | 0.0526          | 0.9202    | 0.9255 | 0.9229 | 0.9881   |
| 0.3555        | 9.46  | 700  | 0.0531          | 0.9197    | 0.9513 | 0.9352 | 0.9862   |
| 0.3555        | 10.81 | 800  | 0.0454          | 0.9167    | 0.9140 | 0.9154 | 0.9872   |
| 0.3555        | 12.16 | 900  | 0.0447          | 0.9284    | 0.9284 | 0.9284 | 0.9895   |
| 0.0479        | 13.51 | 1000 | 0.0436          | 0.9370    | 0.9370 | 0.9370 | 0.9872   |
| 0.0479        | 14.86 | 1100 | 0.0383          | 0.9385    | 0.9628 | 0.9505 | 0.9913   |
| 0.0479        | 16.22 | 1200 | 0.0389          | 0.9468    | 0.9685 | 0.9575 | 0.9908   |
| 0.0479        | 17.57 | 1300 | 0.0349          | 0.9743    | 0.9771 | 0.9757 | 0.9945   |
| 0.0479        | 18.92 | 1400 | 0.0329          | 0.9885    | 0.9857 | 0.9871 | 0.9954   |
| 0.0244        | 20.27 | 1500 | 0.0380          | 0.9412    | 0.9628 | 0.9518 | 0.9917   |
| 0.0244        | 21.62 | 1600 | 0.0447          | 0.8917    | 0.9198 | 0.9055 | 0.9853   |
| 0.0244        | 22.97 | 1700 | 0.0434          | 0.9148    | 0.9542 | 0.9341 | 0.9876   |
| 0.0244        | 24.32 | 1800 | 0.0444          | 0.9280    | 0.9599 | 0.9437 | 0.9890   |
| 0.0244        | 25.68 | 1900 | 0.0386          | 0.9361    | 0.9656 | 0.9506 | 0.9913   |
| 0.015         | 27.03 | 2000 | 0.0381          | 0.9415    | 0.9685 | 0.9548 | 0.9917   |
| 0.015         | 28.38 | 2100 | 0.0341          | 0.9577    | 0.9742 | 0.9659 | 0.9936   |
| 0.015         | 29.73 | 2200 | 0.0340          | 0.9715    | 0.9771 | 0.9743 | 0.9945   |
| 0.015         | 31.08 | 2300 | 0.0365          | 0.9493    | 0.9656 | 0.9574 | 0.9931   |
| 0.015         | 32.43 | 2400 | 0.0398          | 0.9339    | 0.9713 | 0.9522 | 0.9913   |
| 0.0123        | 33.78 | 2500 | 0.0375          | 0.9443    | 0.9713 | 0.9576 | 0.9927   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["sroie"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "sogemi_ddt_1.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.9442896935933147, "name": "Precision"}, {"type": "recall", "value": 0.9713467048710601, "name": "Recall"}, {"type": "f1", "value": 0.9576271186440677, "name": "F1"}, {"type": "accuracy", "value": 0.9926639156350298, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:sroie license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

sogemi\_ddt\_1.0
================


This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0375
* Precision: 0.9443
* Recall: 0.9713
* F1: 0.9576
* Accuracy: 0.9927


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: 2500


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2



### 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: 2500 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### 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: 2500 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### 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: 2500### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.2.2
* Tokenizers 0.13.2