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# LayoutLMv3_5_entities_filtred_14

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: 1.7320
- Precision: 0.3448
- Recall: 0.5
- F1: 0.4082
- Accuracy: 0.7818

## 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        | 50.0   | 100  | 1.1811          | 0.25      | 0.35   | 0.2917 | 0.7545   |
| No log        | 100.0  | 200  | 1.2562          | 0.3571    | 0.5    | 0.4167 | 0.7818   |
| No log        | 150.0  | 300  | 1.3252          | 0.3571    | 0.5    | 0.4167 | 0.7818   |
| No log        | 200.0  | 400  | 1.4481          | 0.3214    | 0.45   | 0.375  | 0.7727   |
| 0.0915        | 250.0  | 500  | 1.4329          | 0.3214    | 0.45   | 0.375  | 0.7727   |
| 0.0915        | 300.0  | 600  | 1.5575          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0915        | 350.0  | 700  | 1.5278          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0915        | 400.0  | 800  | 1.5534          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0915        | 450.0  | 900  | 1.6201          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0008        | 500.0  | 1000 | 1.6480          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0008        | 550.0  | 1100 | 1.6600          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0008        | 600.0  | 1200 | 1.6805          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0008        | 650.0  | 1300 | 1.6968          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0008        | 700.0  | 1400 | 1.7047          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0005        | 750.0  | 1500 | 1.7090          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0005        | 800.0  | 1600 | 1.7173          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0005        | 850.0  | 1700 | 1.7268          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0005        | 900.0  | 1800 | 1.7318          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0005        | 950.0  | 1900 | 1.7327          | 0.3448    | 0.5    | 0.4082 | 0.7818   |
| 0.0004        | 1000.0 | 2000 | 1.7320          | 0.3448    | 0.5    | 0.4082 | 0.7818   |


### 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_14", "results": []}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us