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# LayoutLMv3_5_entities_filtred_21

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2156
- Precision: 0.5
- Recall: 0.4925
- F1: 0.4962
- Accuracy: 0.8423

## 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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 10.0  | 100  | 0.8223          | 0.3333    | 0.2239 | 0.2679 | 0.8054   |
| No log        | 20.0  | 200  | 0.8614          | 0.4328    | 0.4328 | 0.4328 | 0.8221   |
| No log        | 30.0  | 300  | 0.9427          | 0.5522    | 0.5522 | 0.5522 | 0.8456   |
| No log        | 40.0  | 400  | 0.9633          | 0.5075    | 0.5075 | 0.5075 | 0.8356   |
| 0.3534        | 50.0  | 500  | 0.9632          | 0.5323    | 0.4925 | 0.5116 | 0.8490   |
| 0.3534        | 60.0  | 600  | 1.0486          | 0.5224    | 0.5224 | 0.5224 | 0.8456   |
| 0.3534        | 70.0  | 700  | 1.0959          | 0.4921    | 0.4627 | 0.4769 | 0.8356   |
| 0.3534        | 80.0  | 800  | 1.1039          | 0.5224    | 0.5224 | 0.5224 | 0.8389   |
| 0.3534        | 90.0  | 900  | 1.1153          | 0.5312    | 0.5075 | 0.5191 | 0.8423   |
| 0.0067        | 100.0 | 1000 | 1.1449          | 0.4921    | 0.4627 | 0.4769 | 0.8356   |
| 0.0067        | 110.0 | 1100 | 1.1629          | 0.5       | 0.4776 | 0.4885 | 0.8389   |
| 0.0067        | 120.0 | 1200 | 1.1738          | 0.5231    | 0.5075 | 0.5152 | 0.8490   |
| 0.0067        | 130.0 | 1300 | 1.1868          | 0.5385    | 0.5224 | 0.5303 | 0.8523   |
| 0.0067        | 140.0 | 1400 | 1.1994          | 0.5156    | 0.4925 | 0.5038 | 0.8456   |
| 0.0024        | 150.0 | 1500 | 1.2043          | 0.5077    | 0.4925 | 0.5    | 0.8423   |
| 0.0024        | 160.0 | 1600 | 1.2023          | 0.5077    | 0.4925 | 0.5    | 0.8423   |
| 0.0024        | 170.0 | 1700 | 1.2703          | 0.4928    | 0.5075 | 0.5    | 0.8356   |
| 0.0024        | 180.0 | 1800 | 1.2300          | 0.5303    | 0.5224 | 0.5263 | 0.8456   |
| 0.0024        | 190.0 | 1900 | 1.2256          | 0.5152    | 0.5075 | 0.5113 | 0.8423   |
| 0.0019        | 200.0 | 2000 | 1.2156          | 0.5       | 0.4925 | 0.4962 | 0.8423   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "LayoutLMv3_5_entities_filtred_21", "results": []}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us