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# 2024-01-03_one_stage_subgraphs_weighted_txt_vis_conc_6_gate

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2712
- Accuracy: 0.765
- Exit 0 Accuracy: 0.0675
- Exit 1 Accuracy: 0.13

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 24
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Exit 0 Accuracy | Exit 1 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|
| No log        | 0.96  | 16   | 2.6688          | 0.16     | 0.0525          | 0.08            |
| No log        | 1.98  | 33   | 2.4616          | 0.23     | 0.055           | 0.0525          |
| No log        | 3.0   | 50   | 2.2105          | 0.3525   | 0.0575          | 0.0575          |
| No log        | 3.96  | 66   | 1.9883          | 0.42     | 0.0575          | 0.0525          |
| No log        | 4.98  | 83   | 1.7863          | 0.525    | 0.0625          | 0.0575          |
| No log        | 6.0   | 100  | 1.4980          | 0.6125   | 0.0675          | 0.04            |
| No log        | 6.96  | 116  | 1.3248          | 0.6475   | 0.0675          | 0.055           |
| No log        | 7.98  | 133  | 1.1715          | 0.6875   | 0.065           | 0.0625          |
| No log        | 9.0   | 150  | 1.0884          | 0.6975   | 0.0675          | 0.0625          |
| No log        | 9.96  | 166  | 1.0221          | 0.725    | 0.0675          | 0.0525          |
| No log        | 10.98 | 183  | 0.9646          | 0.7375   | 0.0675          | 0.0475          |
| No log        | 12.0  | 200  | 0.9562          | 0.75     | 0.065           | 0.0525          |
| No log        | 12.96 | 216  | 0.8957          | 0.75     | 0.065           | 0.035           |
| No log        | 13.98 | 233  | 0.9117          | 0.76     | 0.065           | 0.055           |
| No log        | 15.0  | 250  | 0.8972          | 0.765    | 0.065           | 0.0375          |
| No log        | 15.96 | 266  | 0.9015          | 0.765    | 0.065           | 0.05            |
| No log        | 16.98 | 283  | 0.9712          | 0.7625   | 0.0675          | 0.04            |
| No log        | 18.0  | 300  | 0.9805          | 0.755    | 0.0675          | 0.0825          |
| No log        | 18.96 | 316  | 0.9794          | 0.7525   | 0.0675          | 0.05            |
| No log        | 19.98 | 333  | 1.0191          | 0.75     | 0.0675          | 0.0575          |
| No log        | 21.0  | 350  | 1.0427          | 0.745    | 0.0675          | 0.0725          |
| No log        | 21.96 | 366  | 0.9744          | 0.77     | 0.065           | 0.0925          |
| No log        | 22.98 | 383  | 1.0432          | 0.7575   | 0.065           | 0.115           |
| No log        | 24.0  | 400  | 1.0682          | 0.7625   | 0.065           | 0.105           |
| No log        | 24.96 | 416  | 1.0981          | 0.7675   | 0.0675          | 0.1175          |
| No log        | 25.98 | 433  | 1.1199          | 0.765    | 0.0675          | 0.1075          |
| No log        | 27.0  | 450  | 1.1305          | 0.76     | 0.0675          | 0.1075          |
| No log        | 27.96 | 466  | 1.1391          | 0.7625   | 0.0675          | 0.1125          |
| No log        | 28.98 | 483  | 1.1646          | 0.765    | 0.0675          | 0.095           |
| 0.3865        | 30.0  | 500  | 1.1655          | 0.7625   | 0.0675          | 0.0975          |
| 0.3865        | 30.96 | 516  | 1.1787          | 0.75     | 0.0675          | 0.1025          |
| 0.3865        | 31.98 | 533  | 1.1661          | 0.7725   | 0.0675          | 0.11            |
| 0.3865        | 33.0  | 550  | 1.1744          | 0.7725   | 0.0675          | 0.11            |
| 0.3865        | 33.96 | 566  | 1.2073          | 0.77     | 0.0675          | 0.095           |
| 0.3865        | 34.98 | 583  | 1.2425          | 0.75     | 0.0675          | 0.09            |
| 0.3865        | 36.0  | 600  | 1.2566          | 0.7525   | 0.0675          | 0.0825          |
| 0.3865        | 36.96 | 616  | 1.2562          | 0.7525   | 0.0675          | 0.085           |
| 0.3865        | 37.98 | 633  | 1.2366          | 0.75     | 0.0675          | 0.0825          |
| 0.3865        | 39.0  | 650  | 1.2024          | 0.77     | 0.0675          | 0.0825          |
| 0.3865        | 39.96 | 666  | 1.2182          | 0.7675   | 0.0675          | 0.09            |
| 0.3865        | 40.98 | 683  | 1.2355          | 0.7575   | 0.0675          | 0.0825          |
| 0.3865        | 42.0  | 700  | 1.2351          | 0.765    | 0.0675          | 0.09            |
| 0.3865        | 42.96 | 716  | 1.2479          | 0.7575   | 0.0675          | 0.1025          |
| 0.3865        | 43.98 | 733  | 1.2311          | 0.7675   | 0.0675          | 0.105           |
| 0.3865        | 45.0  | 750  | 1.2517          | 0.765    | 0.0675          | 0.0975          |
| 0.3865        | 45.96 | 766  | 1.2442          | 0.7675   | 0.0675          | 0.1025          |
| 0.3865        | 46.98 | 783  | 1.2380          | 0.765    | 0.0675          | 0.11            |
| 0.3865        | 48.0  | 800  | 1.2502          | 0.77     | 0.0675          | 0.1025          |
| 0.3865        | 48.96 | 816  | 1.2488          | 0.77     | 0.0675          | 0.1025          |
| 0.3865        | 49.98 | 833  | 1.2498          | 0.77     | 0.0675          | 0.105           |
| 0.3865        | 51.0  | 850  | 1.2554          | 0.7725   | 0.0675          | 0.12            |
| 0.3865        | 51.96 | 866  | 1.2683          | 0.7625   | 0.0675          | 0.1225          |
| 0.3865        | 52.98 | 883  | 1.2607          | 0.7675   | 0.0675          | 0.1325          |
| 0.3865        | 54.0  | 900  | 1.2689          | 0.765    | 0.0675          | 0.13            |
| 0.3865        | 54.96 | 916  | 1.2597          | 0.765    | 0.0675          | 0.13            |
| 0.3865        | 55.98 | 933  | 1.2672          | 0.7675   | 0.0675          | 0.125           |
| 0.3865        | 57.0  | 950  | 1.2714          | 0.765    | 0.0675          | 0.13            |
| 0.3865        | 57.6  | 960  | 1.2712          | 0.765    | 0.0675          | 0.13            |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/layoutlmv3-base", "model-index": [{"name": "2024-01-03_one_stage_subgraphs_weighted_txt_vis_conc_6_gate", "results": []}]}
transformers pytorch tensorboard layoutlmv3 text-classification generated_from_trainer base_model:microsoft/layoutlmv3-base license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us