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# 2024-01-09_one_stage_subgraphs_weighted_entropyreg_txt_vis_conc_1_4_8_12_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: 1.0736
- Accuracy: 0.755
- Exit 0 Accuracy: 0.0625
- Exit 1 Accuracy: 0.0725
- Exit 2 Accuracy: 0.0625
- Exit 3 Accuracy: 0.0625
- Exit 4 Accuracy: 0.755

## 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 | Exit 2 Accuracy | Exit 3 Accuracy | Exit 4 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|
| No log        | 0.96  | 16   | 2.6720          | 0.1675   | 0.06            | 0.08            | 0.0625          | 0.0625          | 0.1675          |
| No log        | 1.98  | 33   | 2.5560          | 0.235    | 0.06            | 0.0725          | 0.0625          | 0.0625          | 0.235           |
| No log        | 3.0   | 50   | 2.4719          | 0.2475   | 0.0675          | 0.0775          | 0.0625          | 0.0625          | 0.2475          |
| No log        | 3.96  | 66   | 2.3389          | 0.31     | 0.0675          | 0.08            | 0.0625          | 0.0625          | 0.31            |
| No log        | 4.98  | 83   | 2.2557          | 0.34     | 0.07            | 0.0775          | 0.0625          | 0.0625          | 0.34            |
| No log        | 6.0   | 100  | 2.2581          | 0.3075   | 0.07            | 0.0675          | 0.0625          | 0.0625          | 0.3075          |
| No log        | 6.96  | 116  | 2.0395          | 0.4175   | 0.065           | 0.0675          | 0.0625          | 0.0625          | 0.4175          |
| No log        | 7.98  | 133  | 1.8828          | 0.5025   | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.5025          |
| No log        | 9.0   | 150  | 1.7408          | 0.545    | 0.0625          | 0.0775          | 0.0625          | 0.0625          | 0.545           |
| No log        | 9.96  | 166  | 1.5987          | 0.5975   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.5975          |
| No log        | 10.98 | 183  | 1.4925          | 0.63     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.63            |
| No log        | 12.0  | 200  | 1.2624          | 0.705    | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.705           |
| No log        | 12.96 | 216  | 1.2142          | 0.7125   | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.7125          |
| No log        | 13.98 | 233  | 1.1393          | 0.7225   | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.7225          |
| No log        | 15.0  | 250  | 1.1158          | 0.7125   | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.7125          |
| No log        | 15.96 | 266  | 1.0664          | 0.7075   | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.7075          |
| No log        | 16.98 | 283  | 1.0757          | 0.7325   | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.7325          |
| No log        | 18.0  | 300  | 1.0319          | 0.73     | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.73            |
| No log        | 18.96 | 316  | 1.0531          | 0.735    | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.735           |
| No log        | 19.98 | 333  | 1.0393          | 0.72     | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.72            |
| No log        | 21.0  | 350  | 1.0517          | 0.7225   | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.7225          |
| No log        | 21.96 | 366  | 1.0466          | 0.73     | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.73            |
| No log        | 22.98 | 383  | 1.0608          | 0.7275   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7275          |
| No log        | 24.0  | 400  | 1.0289          | 0.7325   | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.7325          |
| No log        | 24.96 | 416  | 1.0302          | 0.7375   | 0.0625          | 0.0675          | 0.0625          | 0.0625          | 0.7375          |
| No log        | 25.98 | 433  | 1.0541          | 0.7325   | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.7325          |
| No log        | 27.0  | 450  | 1.0866          | 0.7375   | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.7375          |
| No log        | 27.96 | 466  | 1.0708          | 0.725    | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.725           |
| No log        | 28.98 | 483  | 1.0817          | 0.735    | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.735           |
| 0.5648        | 30.0  | 500  | 1.0515          | 0.74     | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.74            |
| 0.5648        | 30.96 | 516  | 1.0553          | 0.735    | 0.0625          | 0.065           | 0.0625          | 0.0625          | 0.735           |
| 0.5648        | 31.98 | 533  | 1.0368          | 0.7475   | 0.0625          | 0.0625          | 0.0625          | 0.0625          | 0.7475          |
| 0.5648        | 33.0  | 550  | 1.0459          | 0.75     | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 33.96 | 566  | 1.0581          | 0.745    | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.745           |
| 0.5648        | 34.98 | 583  | 1.0532          | 0.7525   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 36.0  | 600  | 1.0679          | 0.75     | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 36.96 | 616  | 1.0850          | 0.7425   | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.7425          |
| 0.5648        | 37.98 | 633  | 1.0780          | 0.755    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.755           |
| 0.5648        | 39.0  | 650  | 1.0592          | 0.75     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 39.96 | 666  | 1.0790          | 0.75     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 40.98 | 683  | 1.0661          | 0.7525   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 42.0  | 700  | 1.0841          | 0.7475   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7475          |
| 0.5648        | 42.96 | 716  | 1.0792          | 0.7475   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7475          |
| 0.5648        | 43.98 | 733  | 1.0659          | 0.7525   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 45.0  | 750  | 1.0794          | 0.75     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 45.96 | 766  | 1.0712          | 0.745    | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.745           |
| 0.5648        | 46.98 | 783  | 1.0714          | 0.745    | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.745           |
| 0.5648        | 48.0  | 800  | 1.0710          | 0.75     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 48.96 | 816  | 1.0711          | 0.75     | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.75            |
| 0.5648        | 49.98 | 833  | 1.0669          | 0.7525   | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 51.0  | 850  | 1.0751          | 0.7525   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 51.96 | 866  | 1.0712          | 0.7575   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7575          |
| 0.5648        | 52.98 | 883  | 1.0700          | 0.7525   | 0.0625          | 0.07            | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 54.0  | 900  | 1.0707          | 0.7525   | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.7525          |
| 0.5648        | 54.96 | 916  | 1.0718          | 0.755    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.755           |
| 0.5648        | 55.98 | 933  | 1.0732          | 0.755    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.755           |
| 0.5648        | 57.0  | 950  | 1.0736          | 0.755    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.755           |
| 0.5648        | 57.6  | 960  | 1.0736          | 0.755    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.755           |


### 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": "2024-01-09_one_stage_subgraphs_weighted_entropyreg_txt_vis_conc_1_4_8_12_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