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# manifesti_v2.1

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: 0.0124
- Precision: 0.9700
- Recall: 0.9727
- F1: 0.9714
- Accuracy: 0.9978

## 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        | 0.31  | 100  | 0.0854          | 0.7703    | 0.7569 | 0.7636 | 0.9791   |
| No log        | 0.61  | 200  | 0.0417          | 0.916     | 0.8613 | 0.8878 | 0.9899   |
| No log        | 0.92  | 300  | 0.0384          | 0.8650    | 0.9064 | 0.8852 | 0.9897   |
| No log        | 1.23  | 400  | 0.0197          | 0.9521    | 0.9431 | 0.9476 | 0.9954   |
| 0.1223        | 1.53  | 500  | 0.0148          | 0.9567    | 0.9652 | 0.9609 | 0.9965   |
| 0.1223        | 1.84  | 600  | 0.0174          | 0.9495    | 0.9643 | 0.9568 | 0.9966   |
| 0.1223        | 2.15  | 700  | 0.0159          | 0.9564    | 0.9685 | 0.9624 | 0.9967   |
| 0.1223        | 2.45  | 800  | 0.0131          | 0.9691    | 0.9727 | 0.9709 | 0.9977   |
| 0.1223        | 2.76  | 900  | 0.0124          | 0.9632    | 0.9723 | 0.9677 | 0.9976   |
| 0.0133        | 3.07  | 1000 | 0.0116          | 0.9802    | 0.9756 | 0.9779 | 0.9982   |
| 0.0133        | 3.37  | 1100 | 0.0118          | 0.9701    | 0.9746 | 0.9723 | 0.9979   |
| 0.0133        | 3.68  | 1200 | 0.0116          | 0.9709    | 0.9737 | 0.9723 | 0.9978   |
| 0.0133        | 3.99  | 1300 | 0.0118          | 0.9700    | 0.9727 | 0.9714 | 0.9979   |
| 0.0133        | 4.29  | 1400 | 0.0131          | 0.9691    | 0.9727 | 0.9709 | 0.9975   |
| 0.0067        | 4.6   | 1500 | 0.0121          | 0.9700    | 0.9727 | 0.9714 | 0.9979   |
| 0.0067        | 4.91  | 1600 | 0.0133          | 0.9663    | 0.9713 | 0.9688 | 0.9975   |
| 0.0067        | 5.21  | 1700 | 0.0121          | 0.9709    | 0.9727 | 0.9718 | 0.9979   |
| 0.0067        | 5.52  | 1800 | 0.0124          | 0.9718    | 0.9737 | 0.9728 | 0.9979   |
| 0.0067        | 5.83  | 1900 | 0.0123          | 0.9700    | 0.9727 | 0.9714 | 0.9978   |
| 0.0048        | 6.13  | 2000 | 0.0124          | 0.9700    | 0.9727 | 0.9714 | 0.9978   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- 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": "manifesti_v2.1", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "sroie", "type": "sroie", "config": "discharge", "split": "test", "args": "discharge"}, "metrics": [{"type": "precision", "value": 0.9699953117674637, "name": "Precision"}, {"type": "recall", "value": 0.9727315467795017, "name": "Recall"}, {"type": "f1", "value": 0.9713615023474178, "name": "F1"}, {"type": "accuracy", "value": 0.9978122615110658, "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