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# 2024-01-09_one_stage_subgraphs_weighted_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: 1.2598
- Accuracy: 0.7825
- Exit 0 Accuracy: 0.2725
- Exit 1 Accuracy: 0.7725

## 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   | 2.6838          | 0.13     | 0.1275          | 0.0675          |
| No log        | 1.98  | 33   | 2.5115          | 0.2275   | 0.125           | 0.1             |
| No log        | 3.0   | 50   | 2.2857          | 0.3075   | 0.1525          | 0.15            |
| No log        | 3.96  | 66   | 2.0132          | 0.4075   | 0.1525          | 0.3225          |
| No log        | 4.98  | 83   | 1.7290          | 0.5375   | 0.1525          | 0.385           |
| No log        | 6.0   | 100  | 1.4748          | 0.605    | 0.155           | 0.4175          |
| No log        | 6.96  | 116  | 1.2413          | 0.7275   | 0.155           | 0.5475          |
| No log        | 7.98  | 133  | 1.1173          | 0.745    | 0.1675          | 0.535           |
| No log        | 9.0   | 150  | 0.9922          | 0.7525   | 0.19            | 0.565           |
| No log        | 9.96  | 166  | 0.9208          | 0.765    | 0.2025          | 0.5525          |
| No log        | 10.98 | 183  | 0.9245          | 0.7625   | 0.2075          | 0.62            |
| No log        | 12.0  | 200  | 0.8917          | 0.765    | 0.2025          | 0.6525          |
| No log        | 12.96 | 216  | 0.8648          | 0.7625   | 0.1975          | 0.6525          |
| No log        | 13.98 | 233  | 0.8759          | 0.775    | 0.2075          | 0.685           |
| No log        | 15.0  | 250  | 0.9405          | 0.77     | 0.215           | 0.6825          |
| No log        | 15.96 | 266  | 0.9411          | 0.7725   | 0.21            | 0.6975          |
| No log        | 16.98 | 283  | 0.9830          | 0.7625   | 0.2225          | 0.6925          |
| No log        | 18.0  | 300  | 0.9696          | 0.775    | 0.2275          | 0.735           |
| No log        | 18.96 | 316  | 0.9827          | 0.78     | 0.23            | 0.7375          |
| No log        | 19.98 | 333  | 1.0221          | 0.78     | 0.235           | 0.755           |
| No log        | 21.0  | 350  | 1.0305          | 0.77     | 0.2225          | 0.7475          |
| No log        | 21.96 | 366  | 1.0608          | 0.775    | 0.2125          | 0.7325          |
| No log        | 22.98 | 383  | 1.0518          | 0.7825   | 0.235           | 0.7575          |
| No log        | 24.0  | 400  | 1.0250          | 0.7875   | 0.24            | 0.76            |
| No log        | 24.96 | 416  | 1.0568          | 0.79     | 0.2425          | 0.7675          |
| No log        | 25.98 | 433  | 1.0601          | 0.7875   | 0.265           | 0.765           |
| No log        | 27.0  | 450  | 1.0849          | 0.7925   | 0.25            | 0.7625          |
| No log        | 27.96 | 466  | 1.0939          | 0.78     | 0.2675          | 0.7625          |
| No log        | 28.98 | 483  | 1.1370          | 0.7825   | 0.265           | 0.77            |
| 0.8593        | 30.0  | 500  | 1.1109          | 0.785    | 0.26            | 0.7575          |
| 0.8593        | 30.96 | 516  | 1.1332          | 0.7825   | 0.2675          | 0.7625          |
| 0.8593        | 31.98 | 533  | 1.1221          | 0.7875   | 0.2675          | 0.7725          |
| 0.8593        | 33.0  | 550  | 1.1503          | 0.7775   | 0.265           | 0.7575          |
| 0.8593        | 33.96 | 566  | 1.1640          | 0.7825   | 0.265           | 0.77            |
| 0.8593        | 34.98 | 583  | 1.1430          | 0.79     | 0.2625          | 0.7675          |
| 0.8593        | 36.0  | 600  | 1.1700          | 0.7825   | 0.265           | 0.775           |
| 0.8593        | 36.96 | 616  | 1.1895          | 0.7775   | 0.2625          | 0.755           |
| 0.8593        | 37.98 | 633  | 1.1890          | 0.7825   | 0.27            | 0.77            |
| 0.8593        | 39.0  | 650  | 1.1726          | 0.7925   | 0.2675          | 0.76            |
| 0.8593        | 39.96 | 666  | 1.2200          | 0.775    | 0.2725          | 0.7725          |
| 0.8593        | 40.98 | 683  | 1.1801          | 0.785    | 0.2725          | 0.76            |
| 0.8593        | 42.0  | 700  | 1.2199          | 0.7825   | 0.27            | 0.77            |
| 0.8593        | 42.96 | 716  | 1.2134          | 0.785    | 0.27            | 0.765           |
| 0.8593        | 43.98 | 733  | 1.2167          | 0.78     | 0.275           | 0.77            |
| 0.8593        | 45.0  | 750  | 1.2335          | 0.78     | 0.27            | 0.7625          |
| 0.8593        | 45.96 | 766  | 1.2210          | 0.785    | 0.2775          | 0.7725          |
| 0.8593        | 46.98 | 783  | 1.2367          | 0.7825   | 0.275           | 0.77            |
| 0.8593        | 48.0  | 800  | 1.2342          | 0.78     | 0.27            | 0.77            |
| 0.8593        | 48.96 | 816  | 1.2450          | 0.7825   | 0.275           | 0.7675          |
| 0.8593        | 49.98 | 833  | 1.2485          | 0.785    | 0.2775          | 0.7625          |
| 0.8593        | 51.0  | 850  | 1.2715          | 0.78     | 0.275           | 0.7675          |
| 0.8593        | 51.96 | 866  | 1.2942          | 0.78     | 0.2775          | 0.7675          |
| 0.8593        | 52.98 | 883  | 1.2706          | 0.7825   | 0.2725          | 0.7625          |
| 0.8593        | 54.0  | 900  | 1.2566          | 0.78     | 0.275           | 0.765           |
| 0.8593        | 54.96 | 916  | 1.2581          | 0.78     | 0.2725          | 0.775           |
| 0.8593        | 55.98 | 933  | 1.2589          | 0.7825   | 0.2725          | 0.775           |
| 0.8593        | 57.0  | 950  | 1.2596          | 0.7825   | 0.2725          | 0.7725          |
| 0.8593        | 57.6  | 960  | 1.2598          | 0.7825   | 0.2725          | 0.7725          |


### 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_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