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# 2024-01-06_one_stage_subgraphs_weighted_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: 1.1285
- Accuracy: 0.7775
- Exit 0 Accuracy: 0.035
- Exit 1 Accuracy: 0.065
- Exit 2 Accuracy: 0.0625
- Exit 3 Accuracy: 0.0625
- Exit 4 Accuracy: 0.7775

## 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   | 2.6521          | 0.185    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.185           |
| No log        | 1.98  | 33   | 2.5024          | 0.225    | 0.0625          | 0.0725          | 0.0625          | 0.0625          | 0.225           |
| No log        | 3.0   | 50   | 2.3005          | 0.2825   | 0.0525          | 0.085           | 0.0625          | 0.0625          | 0.2825          |
| No log        | 3.96  | 66   | 2.0909          | 0.38     | 0.0475          | 0.075           | 0.0625          | 0.0625          | 0.38            |
| No log        | 4.98  | 83   | 1.8878          | 0.4675   | 0.045           | 0.065           | 0.0625          | 0.0625          | 0.4675          |
| No log        | 6.0   | 100  | 1.6333          | 0.56     | 0.035           | 0.0625          | 0.0625          | 0.0625          | 0.56            |
| No log        | 6.96  | 116  | 1.4491          | 0.625    | 0.035           | 0.0625          | 0.0625          | 0.0625          | 0.625           |
| No log        | 7.98  | 133  | 1.2641          | 0.6625   | 0.03            | 0.0625          | 0.0625          | 0.0625          | 0.6625          |
| No log        | 9.0   | 150  | 1.1697          | 0.6875   | 0.035           | 0.0625          | 0.0625          | 0.0625          | 0.6875          |
| No log        | 9.96  | 166  | 1.0498          | 0.7275   | 0.03            | 0.0625          | 0.0625          | 0.0625          | 0.7275          |
| No log        | 10.98 | 183  | 1.0408          | 0.715    | 0.03            | 0.0625          | 0.0625          | 0.0625          | 0.715           |
| No log        | 12.0  | 200  | 0.9298          | 0.7575   | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.7575          |
| No log        | 12.96 | 216  | 0.9264          | 0.7425   | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.7425          |
| No log        | 13.98 | 233  | 0.9073          | 0.7475   | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.7475          |
| No log        | 15.0  | 250  | 0.8787          | 0.7525   | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.7525          |
| No log        | 15.96 | 266  | 0.9141          | 0.755    | 0.0375          | 0.06            | 0.0625          | 0.0625          | 0.755           |
| No log        | 16.98 | 283  | 0.9292          | 0.7475   | 0.0375          | 0.0525          | 0.0625          | 0.0625          | 0.7475          |
| No log        | 18.0  | 300  | 0.9011          | 0.7725   | 0.0375          | 0.0475          | 0.0625          | 0.0625          | 0.7725          |
| No log        | 18.96 | 316  | 0.9439          | 0.765    | 0.0375          | 0.05            | 0.0625          | 0.0625          | 0.765           |
| No log        | 19.98 | 333  | 0.9692          | 0.7675   | 0.04            | 0.0575          | 0.0625          | 0.0625          | 0.7675          |
| No log        | 21.0  | 350  | 0.9501          | 0.775    | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.775           |
| No log        | 21.96 | 366  | 0.9702          | 0.7725   | 0.035           | 0.06            | 0.0625          | 0.0625          | 0.7725          |
| No log        | 22.98 | 383  | 1.0124          | 0.7675   | 0.0425          | 0.06            | 0.0625          | 0.0625          | 0.7675          |
| No log        | 24.0  | 400  | 0.9772          | 0.78     | 0.0375          | 0.06            | 0.0625          | 0.0625          | 0.78            |
| No log        | 24.96 | 416  | 1.0035          | 0.7725   | 0.0375          | 0.06            | 0.0625          | 0.0625          | 0.7725          |
| No log        | 25.98 | 433  | 1.0374          | 0.77     | 0.0375          | 0.06            | 0.0625          | 0.0625          | 0.77            |
| No log        | 27.0  | 450  | 1.0284          | 0.7675   | 0.0375          | 0.0625          | 0.0625          | 0.0625          | 0.7675          |
| No log        | 27.96 | 466  | 1.0110          | 0.7825   | 0.04            | 0.0625          | 0.0625          | 0.0625          | 0.7825          |
| No log        | 28.98 | 483  | 1.0291          | 0.7725   | 0.04            | 0.0625          | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 30.0  | 500  | 1.0285          | 0.775    | 0.04            | 0.0625          | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 30.96 | 516  | 1.0399          | 0.7775   | 0.04            | 0.0625          | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 31.98 | 533  | 1.0550          | 0.78     | 0.04            | 0.0625          | 0.0625          | 0.0625          | 0.78            |
| 0.3746        | 33.0  | 550  | 1.0606          | 0.7775   | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 33.96 | 566  | 1.0618          | 0.7775   | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 34.98 | 583  | 1.0651          | 0.7825   | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.7825          |
| 0.3746        | 36.0  | 600  | 1.0646          | 0.775    | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 36.96 | 616  | 1.0777          | 0.775    | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 37.98 | 633  | 1.0896          | 0.7725   | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 39.0  | 650  | 1.0834          | 0.785    | 0.04            | 0.065           | 0.0625          | 0.0625          | 0.785           |
| 0.3746        | 39.96 | 666  | 1.0875          | 0.78     | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.78            |
| 0.3746        | 40.98 | 683  | 1.0831          | 0.7825   | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.7825          |
| 0.3746        | 42.0  | 700  | 1.0980          | 0.78     | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.78            |
| 0.3746        | 42.96 | 716  | 1.1054          | 0.7725   | 0.0375          | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 43.98 | 733  | 1.1083          | 0.7725   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 45.0  | 750  | 1.1166          | 0.775    | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 45.96 | 766  | 1.1093          | 0.775    | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 46.98 | 783  | 1.1114          | 0.7725   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 48.0  | 800  | 1.1183          | 0.7725   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 48.96 | 816  | 1.1178          | 0.7725   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 49.98 | 833  | 1.1169          | 0.775    | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 51.0  | 850  | 1.1187          | 0.7725   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7725          |
| 0.3746        | 51.96 | 866  | 1.1183          | 0.7775   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 52.98 | 883  | 1.1227          | 0.775    | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.775           |
| 0.3746        | 54.0  | 900  | 1.1253          | 0.78     | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.78            |
| 0.3746        | 54.96 | 916  | 1.1269          | 0.7775   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 55.98 | 933  | 1.1279          | 0.7775   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 57.0  | 950  | 1.1283          | 0.7775   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7775          |
| 0.3746        | 57.6  | 960  | 1.1285          | 0.7775   | 0.035           | 0.065           | 0.0625          | 0.0625          | 0.7775          |


### 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": "2024-01-06_one_stage_subgraphs_weighted_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