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# Bol1.0

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: 0.5251
- Precision: 0.5769
- Recall: 0.5
- F1: 0.5357
- Accuracy: 0.9027

## 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        | 1.61  | 100  | 2.0701          | 0.0476    | 0.0333 | 0.0392 | 0.3717   |
| No log        | 3.23  | 200  | 1.5988          | 0.1852    | 0.1667 | 0.1754 | 0.6726   |
| No log        | 4.84  | 300  | 1.2027          | 0.3846    | 0.3333 | 0.3571 | 0.6726   |
| No log        | 6.45  | 400  | 0.9370          | 0.45      | 0.3    | 0.3600 | 0.8142   |
| 0.7987        | 8.06  | 500  | 0.7833          | 0.3333    | 0.2667 | 0.2963 | 0.8230   |
| 0.7987        | 9.68  | 600  | 0.6820          | 0.4348    | 0.3333 | 0.3774 | 0.8319   |
| 0.7987        | 11.29 | 700  | 0.6220          | 0.4074    | 0.3667 | 0.3860 | 0.8319   |
| 0.7987        | 12.9  | 800  | 0.5621          | 0.4815    | 0.4333 | 0.4561 | 0.8496   |
| 0.7987        | 14.52 | 900  | 0.5351          | 0.5       | 0.4667 | 0.4828 | 0.8938   |
| 0.2748        | 16.13 | 1000 | 0.5251          | 0.5769    | 0.5    | 0.5357 | 0.9027   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.2.2
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["sroie"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "Bol1.0", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.5769230769230769, "name": "Precision"}, {"type": "recall", "value": 0.5, "name": "Recall"}, {"type": "f1", "value": 0.5357142857142857, "name": "F1"}, {"type": "accuracy", "value": 0.9026548672566371, "name": "Accuracy"}]}]}]}
transformers pytorch layoutlmv3 token-classification generated_from_trainer dataset:sroie license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

Bol1.0
======


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: 0.5251
* Precision: 0.5769
* Recall: 0.5
* F1: 0.5357
* Accuracy: 0.9027


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



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.2.2
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.2.2
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #layoutlmv3 #token-classification #generated_from_trainer #dataset-sroie #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #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: 1000 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.2.2
* Tokenizers 0.13.3