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# 2024-01-12_one_stage_subgraphs_weighted_entropyreg_txt_vis_conc_6_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: 1.4857
- Accuracy: 0.77
- Exit 0 Accuracy: 0.09
- Exit 1 Accuracy: 0.7575

## 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   | 2.6866          | 0.13     | 0.05            | 0.0625          |
| No log        | 1.98  | 33   | 2.5303          | 0.2175   | 0.035           | 0.0625          |
| No log        | 3.0   | 50   | 2.3471          | 0.295    | 0.035           | 0.0625          |
| No log        | 3.96  | 66   | 2.0891          | 0.3975   | 0.0475          | 0.0675          |
| No log        | 4.98  | 83   | 1.7694          | 0.5475   | 0.0475          | 0.0675          |
| No log        | 6.0   | 100  | 1.5006          | 0.6375   | 0.05            | 0.0875          |
| No log        | 6.96  | 116  | 1.3571          | 0.68     | 0.0525          | 0.0875          |
| No log        | 7.98  | 133  | 1.1444          | 0.7475   | 0.0525          | 0.115           |
| No log        | 9.0   | 150  | 1.0465          | 0.73     | 0.055           | 0.1225          |
| No log        | 9.96  | 166  | 0.9712          | 0.75     | 0.06            | 0.15            |
| No log        | 10.98 | 183  | 0.9017          | 0.79     | 0.0675          | 0.16            |
| No log        | 12.0  | 200  | 0.9028          | 0.7675   | 0.065           | 0.1925          |
| No log        | 12.96 | 216  | 0.8929          | 0.78     | 0.065           | 0.21            |
| No log        | 13.98 | 233  | 0.8808          | 0.7725   | 0.075           | 0.2825          |
| No log        | 15.0  | 250  | 0.8962          | 0.7825   | 0.08            | 0.3075          |
| No log        | 15.96 | 266  | 0.9893          | 0.7775   | 0.0825          | 0.3725          |
| No log        | 16.98 | 283  | 1.0809          | 0.7475   | 0.0775          | 0.5             |
| No log        | 18.0  | 300  | 0.9272          | 0.8      | 0.085           | 0.545           |
| No log        | 18.96 | 316  | 1.1704          | 0.7475   | 0.0825          | 0.5875          |
| No log        | 19.98 | 333  | 1.1274          | 0.7725   | 0.0825          | 0.6275          |
| No log        | 21.0  | 350  | 1.1633          | 0.7525   | 0.0825          | 0.6375          |
| No log        | 21.96 | 366  | 1.2537          | 0.76     | 0.085           | 0.6325          |
| No log        | 22.98 | 383  | 1.2364          | 0.7575   | 0.085           | 0.645           |
| No log        | 24.0  | 400  | 1.2045          | 0.7625   | 0.0875          | 0.66            |
| No log        | 24.96 | 416  | 1.2786          | 0.7475   | 0.085           | 0.6575          |
| No log        | 25.98 | 433  | 1.2697          | 0.77     | 0.0875          | 0.6775          |
| No log        | 27.0  | 450  | 1.3530          | 0.7675   | 0.0825          | 0.7025          |
| No log        | 27.96 | 466  | 1.3087          | 0.775    | 0.0825          | 0.7025          |
| No log        | 28.98 | 483  | 1.4329          | 0.7375   | 0.085           | 0.7175          |
| 0.9714        | 30.0  | 500  | 1.3908          | 0.7575   | 0.085           | 0.71            |
| 0.9714        | 30.96 | 516  | 1.4018          | 0.765    | 0.085           | 0.7175          |
| 0.9714        | 31.98 | 533  | 1.3794          | 0.7775   | 0.0875          | 0.7             |
| 0.9714        | 33.0  | 550  | 1.4277          | 0.76     | 0.0875          | 0.725           |
| 0.9714        | 33.96 | 566  | 1.4728          | 0.7575   | 0.09            | 0.73            |
| 0.9714        | 34.98 | 583  | 1.3926          | 0.77     | 0.09            | 0.7375          |
| 0.9714        | 36.0  | 600  | 1.4474          | 0.76     | 0.085           | 0.7425          |
| 0.9714        | 36.96 | 616  | 1.4008          | 0.77     | 0.085           | 0.7475          |
| 0.9714        | 37.98 | 633  | 1.4678          | 0.7575   | 0.085           | 0.7425          |
| 0.9714        | 39.0  | 650  | 1.4913          | 0.7725   | 0.0875          | 0.745           |
| 0.9714        | 39.96 | 666  | 1.4628          | 0.77     | 0.09            | 0.745           |
| 0.9714        | 40.98 | 683  | 1.4442          | 0.7675   | 0.09            | 0.74            |
| 0.9714        | 42.0  | 700  | 1.4448          | 0.7725   | 0.0875          | 0.75            |
| 0.9714        | 42.96 | 716  | 1.5156          | 0.755    | 0.0875          | 0.7425          |
| 0.9714        | 43.98 | 733  | 1.4809          | 0.75     | 0.0875          | 0.7425          |
| 0.9714        | 45.0  | 750  | 1.5115          | 0.7475   | 0.0875          | 0.75            |
| 0.9714        | 45.96 | 766  | 1.4681          | 0.7675   | 0.0925          | 0.755           |
| 0.9714        | 46.98 | 783  | 1.5000          | 0.765    | 0.09            | 0.75            |
| 0.9714        | 48.0  | 800  | 1.4784          | 0.7725   | 0.0875          | 0.755           |
| 0.9714        | 48.96 | 816  | 1.4947          | 0.76     | 0.09            | 0.7525          |
| 0.9714        | 49.98 | 833  | 1.4752          | 0.76     | 0.0875          | 0.7525          |
| 0.9714        | 51.0  | 850  | 1.4891          | 0.7675   | 0.09            | 0.76            |
| 0.9714        | 51.96 | 866  | 1.4876          | 0.7675   | 0.09            | 0.75            |
| 0.9714        | 52.98 | 883  | 1.4789          | 0.7725   | 0.09            | 0.755           |
| 0.9714        | 54.0  | 900  | 1.4820          | 0.765    | 0.09            | 0.7575          |
| 0.9714        | 54.96 | 916  | 1.4797          | 0.775    | 0.09            | 0.7575          |
| 0.9714        | 55.98 | 933  | 1.4880          | 0.77     | 0.09            | 0.76            |
| 0.9714        | 57.0  | 950  | 1.4864          | 0.77     | 0.09            | 0.7575          |
| 0.9714        | 57.6  | 960  | 1.4857          | 0.77     | 0.09            | 0.7575          |


### 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": "2024-01-12_one_stage_subgraphs_weighted_entropyreg_txt_vis_conc_6_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