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# 2024-01-11_one_stage_subgraphs_entropyreg_txt_vis_conc_1_4_8_12_ramp

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: 1.5748
- Accuracy: 0.775
- Exit 0 Accuracy: 0.0675
- Exit 1 Accuracy: 0.405
- Exit 2 Accuracy: 0.6925
- Exit 3 Accuracy: 0.7725
- Exit 4 Accuracy: 0.775

## 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   | 2.6830          | 0.1475   | 0.08            | 0.07            | 0.0625          | 0.0625          | 0.0925          |
| No log        | 1.98  | 33   | 2.5162          | 0.2225   | 0.0875          | 0.115           | 0.0625          | 0.0625          | 0.155           |
| No log        | 3.0   | 50   | 2.3234          | 0.3075   | 0.08            | 0.125           | 0.0625          | 0.0625          | 0.255           |
| No log        | 3.96  | 66   | 2.0222          | 0.4525   | 0.09            | 0.13            | 0.0625          | 0.0625          | 0.38            |
| No log        | 4.98  | 83   | 1.7524          | 0.5625   | 0.085           | 0.125           | 0.0625          | 0.0625          | 0.5025          |
| No log        | 6.0   | 100  | 1.5038          | 0.6175   | 0.08            | 0.12            | 0.0625          | 0.0625          | 0.5475          |
| No log        | 6.96  | 116  | 1.3022          | 0.6775   | 0.085           | 0.1125          | 0.0625          | 0.0625          | 0.6075          |
| No log        | 7.98  | 133  | 1.1943          | 0.7      | 0.0825          | 0.1225          | 0.0625          | 0.0625          | 0.625           |
| No log        | 9.0   | 150  | 1.0962          | 0.7275   | 0.06            | 0.13            | 0.0625          | 0.0625          | 0.65            |
| No log        | 9.96  | 166  | 0.9921          | 0.7375   | 0.07            | 0.125           | 0.0625          | 0.0625          | 0.695           |
| No log        | 10.98 | 183  | 0.9680          | 0.735    | 0.065           | 0.125           | 0.0625          | 0.0625          | 0.725           |
| No log        | 12.0  | 200  | 1.0108          | 0.715    | 0.065           | 0.12            | 0.0625          | 0.0625          | 0.7225          |
| No log        | 12.96 | 216  | 0.9279          | 0.745    | 0.0625          | 0.1325          | 0.0625          | 0.0625          | 0.7375          |
| No log        | 13.98 | 233  | 0.9503          | 0.7375   | 0.0675          | 0.1175          | 0.0625          | 0.0625          | 0.7475          |
| No log        | 15.0  | 250  | 0.9331          | 0.755    | 0.0675          | 0.13            | 0.0625          | 0.0625          | 0.7675          |
| No log        | 15.96 | 266  | 0.9916          | 0.755    | 0.0775          | 0.13            | 0.0625          | 0.0625          | 0.7525          |
| No log        | 16.98 | 283  | 0.9925          | 0.7625   | 0.0775          | 0.13            | 0.075           | 0.0825          | 0.7675          |
| No log        | 18.0  | 300  | 1.0271          | 0.765    | 0.0725          | 0.1375          | 0.08            | 0.1275          | 0.765           |
| No log        | 18.96 | 316  | 1.0369          | 0.78     | 0.0675          | 0.1375          | 0.0725          | 0.2125          | 0.775           |
| No log        | 19.98 | 333  | 1.1098          | 0.755    | 0.06            | 0.1375          | 0.08            | 0.435           | 0.7525          |
| No log        | 21.0  | 350  | 1.1733          | 0.745    | 0.0575          | 0.13            | 0.095           | 0.5625          | 0.7475          |
| No log        | 21.96 | 366  | 1.1522          | 0.765    | 0.055           | 0.1325          | 0.11            | 0.635           | 0.7625          |
| No log        | 22.98 | 383  | 1.1609          | 0.7525   | 0.0575          | 0.1325          | 0.1625          | 0.715           | 0.745           |
| No log        | 24.0  | 400  | 1.1421          | 0.76     | 0.06            | 0.13            | 0.28            | 0.7475          | 0.76            |
| No log        | 24.96 | 416  | 1.3286          | 0.74     | 0.06            | 0.13            | 0.295           | 0.745           | 0.74            |
| No log        | 25.98 | 433  | 1.2456          | 0.76     | 0.0625          | 0.125           | 0.33            | 0.745           | 0.7575          |
| No log        | 27.0  | 450  | 1.2226          | 0.78     | 0.0625          | 0.1225          | 0.3775          | 0.77            | 0.785           |
| No log        | 27.96 | 466  | 1.2414          | 0.77     | 0.0625          | 0.12            | 0.42            | 0.785           | 0.7725          |
| No log        | 28.98 | 483  | 1.3176          | 0.77     | 0.0675          | 0.1575          | 0.43            | 0.7575          | 0.7625          |
| 1.479         | 30.0  | 500  | 1.3033          | 0.77     | 0.0625          | 0.18            | 0.48            | 0.77            | 0.7725          |
| 1.479         | 30.96 | 516  | 1.3519          | 0.78     | 0.065           | 0.19            | 0.515           | 0.7725          | 0.785           |
| 1.479         | 31.98 | 533  | 1.3688          | 0.775    | 0.065           | 0.1925          | 0.5225          | 0.765           | 0.775           |
| 1.479         | 33.0  | 550  | 1.3449          | 0.7725   | 0.065           | 0.2125          | 0.55            | 0.775           | 0.77            |
| 1.479         | 33.96 | 566  | 1.3758          | 0.77     | 0.0675          | 0.235           | 0.59            | 0.7625          | 0.77            |
| 1.479         | 34.98 | 583  | 1.4128          | 0.765    | 0.0675          | 0.2675          | 0.59            | 0.7725          | 0.7625          |
| 1.479         | 36.0  | 600  | 1.4091          | 0.7725   | 0.0675          | 0.31            | 0.5975          | 0.7825          | 0.775           |
| 1.479         | 36.96 | 616  | 1.4275          | 0.77     | 0.0675          | 0.295           | 0.6175          | 0.7725          | 0.7725          |
| 1.479         | 37.98 | 633  | 1.4912          | 0.7625   | 0.0675          | 0.3125          | 0.64            | 0.775           | 0.7625          |
| 1.479         | 39.0  | 650  | 1.4817          | 0.7725   | 0.065           | 0.3275          | 0.6425          | 0.77            | 0.7675          |
| 1.479         | 39.96 | 666  | 1.5270          | 0.7625   | 0.065           | 0.325           | 0.6575          | 0.775           | 0.765           |
| 1.479         | 40.98 | 683  | 1.5566          | 0.76     | 0.065           | 0.335           | 0.66            | 0.7675          | 0.7625          |
| 1.479         | 42.0  | 700  | 1.5411          | 0.76     | 0.065           | 0.36            | 0.6675          | 0.7625          | 0.7625          |
| 1.479         | 42.96 | 716  | 1.5643          | 0.755    | 0.065           | 0.37            | 0.6775          | 0.755           | 0.755           |
| 1.479         | 43.98 | 733  | 1.5261          | 0.765    | 0.065           | 0.365           | 0.6675          | 0.7575          | 0.765           |
| 1.479         | 45.0  | 750  | 1.5265          | 0.7625   | 0.065           | 0.365           | 0.67            | 0.765           | 0.765           |
| 1.479         | 45.96 | 766  | 1.5467          | 0.765    | 0.065           | 0.375           | 0.675           | 0.7725          | 0.765           |
| 1.479         | 46.98 | 783  | 1.5356          | 0.7725   | 0.065           | 0.3775          | 0.66            | 0.775           | 0.7675          |
| 1.479         | 48.0  | 800  | 1.5498          | 0.77     | 0.07            | 0.3825          | 0.6725          | 0.77            | 0.77            |
| 1.479         | 48.96 | 816  | 1.5103          | 0.7775   | 0.065           | 0.38            | 0.69            | 0.7725          | 0.775           |
| 1.479         | 49.98 | 833  | 1.5348          | 0.78     | 0.065           | 0.38            | 0.6825          | 0.775           | 0.78            |
| 1.479         | 51.0  | 850  | 1.5598          | 0.7775   | 0.07            | 0.3875          | 0.675           | 0.7675          | 0.775           |
| 1.479         | 51.96 | 866  | 1.5589          | 0.7775   | 0.065           | 0.4             | 0.6875          | 0.7675          | 0.7775          |
| 1.479         | 52.98 | 883  | 1.5564          | 0.775    | 0.065           | 0.405           | 0.69            | 0.775           | 0.775           |
| 1.479         | 54.0  | 900  | 1.5676          | 0.7725   | 0.065           | 0.3975          | 0.6875          | 0.7725          | 0.775           |
| 1.479         | 54.96 | 916  | 1.5690          | 0.7725   | 0.065           | 0.4025          | 0.6925          | 0.775           | 0.7725          |
| 1.479         | 55.98 | 933  | 1.5814          | 0.7725   | 0.065           | 0.405           | 0.695           | 0.7675          | 0.77            |
| 1.479         | 57.0  | 950  | 1.5753          | 0.775    | 0.0675          | 0.405           | 0.695           | 0.7725          | 0.775           |
| 1.479         | 57.6  | 960  | 1.5748          | 0.775    | 0.0675          | 0.405           | 0.6925          | 0.7725          | 0.775           |


### 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": "2024-01-11_one_stage_subgraphs_entropyreg_txt_vis_conc_1_4_8_12_ramp", "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