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# 2024-01-10_one_stage_subgraphs_weighted_txt_vis_conc_2_5_9_11_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: 1.3189
- Accuracy: 0.7675
- Exit 0 Accuracy: 0.2825
- Exit 1 Accuracy: 0.5075
- Exit 2 Accuracy: 0.7125
- Exit 3 Accuracy: 0.7525
- Exit 4 Accuracy: 0.7625

## 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   | 2.6723          | 0.1675   | 0.07            | 0.0625          | 0.0625          | 0.0625          | 0.0625          |
| No log        | 1.98  | 33   | 2.5058          | 0.2225   | 0.11            | 0.0625          | 0.0625          | 0.0625          | 0.0625          |
| No log        | 3.0   | 50   | 2.2849          | 0.315    | 0.14            | 0.0625          | 0.0625          | 0.0625          | 0.0625          |
| No log        | 3.96  | 66   | 2.0502          | 0.3775   | 0.1425          | 0.0625          | 0.075           | 0.0625          | 0.0625          |
| No log        | 4.98  | 83   | 1.7596          | 0.5525   | 0.15            | 0.0625          | 0.135           | 0.0625          | 0.0625          |
| No log        | 6.0   | 100  | 1.5122          | 0.61     | 0.1525          | 0.0625          | 0.185           | 0.0625          | 0.0625          |
| No log        | 6.96  | 116  | 1.3246          | 0.68     | 0.1575          | 0.0625          | 0.2925          | 0.0625          | 0.0625          |
| No log        | 7.98  | 133  | 1.1676          | 0.73     | 0.16            | 0.0625          | 0.32            | 0.0625          | 0.0625          |
| No log        | 9.0   | 150  | 1.0915          | 0.725    | 0.165           | 0.0625          | 0.37            | 0.0625          | 0.0625          |
| No log        | 9.96  | 166  | 0.9839          | 0.745    | 0.175           | 0.0725          | 0.405           | 0.0625          | 0.095           |
| No log        | 10.98 | 183  | 0.9422          | 0.7475   | 0.19            | 0.07            | 0.43            | 0.0625          | 0.215           |
| No log        | 12.0  | 200  | 0.8930          | 0.75     | 0.2025          | 0.13            | 0.4375          | 0.0625          | 0.34            |
| No log        | 12.96 | 216  | 0.9618          | 0.7475   | 0.1875          | 0.175           | 0.3175          | 0.07            | 0.5275          |
| No log        | 13.98 | 233  | 0.9134          | 0.755    | 0.21            | 0.1275          | 0.405           | 0.115           | 0.675           |
| No log        | 15.0  | 250  | 0.9206          | 0.7625   | 0.225           | 0.215           | 0.3775          | 0.2025          | 0.72            |
| No log        | 15.96 | 266  | 0.9201          | 0.7675   | 0.225           | 0.0825          | 0.4325          | 0.265           | 0.765           |
| No log        | 16.98 | 283  | 0.9146          | 0.765    | 0.2325          | 0.1675          | 0.4075          | 0.4175          | 0.7325          |
| No log        | 18.0  | 300  | 0.9194          | 0.785    | 0.24            | 0.1575          | 0.4575          | 0.3             | 0.775           |
| No log        | 18.96 | 316  | 0.9924          | 0.765    | 0.25            | 0.22            | 0.53            | 0.5325          | 0.7475          |
| No log        | 19.98 | 333  | 1.0287          | 0.76     | 0.245           | 0.2125          | 0.5175          | 0.6             | 0.7525          |
| No log        | 21.0  | 350  | 1.0235          | 0.78     | 0.245           | 0.2175          | 0.555           | 0.645           | 0.78            |
| No log        | 21.96 | 366  | 1.0739          | 0.7525   | 0.2275          | 0.2775          | 0.57            | 0.69            | 0.7575          |
| No log        | 22.98 | 383  | 1.0812          | 0.77     | 0.2425          | 0.26            | 0.585           | 0.73            | 0.775           |
| No log        | 24.0  | 400  | 1.1115          | 0.7625   | 0.2475          | 0.1575          | 0.6425          | 0.765           | 0.7675          |
| No log        | 24.96 | 416  | 1.1116          | 0.7775   | 0.265           | 0.21            | 0.64            | 0.7675          | 0.77            |
| No log        | 25.98 | 433  | 1.1361          | 0.7675   | 0.2625          | 0.2525          | 0.6575          | 0.765           | 0.7675          |
| No log        | 27.0  | 450  | 1.1371          | 0.78     | 0.2525          | 0.2625          | 0.6525          | 0.7725          | 0.7725          |
| No log        | 27.96 | 466  | 1.1591          | 0.765    | 0.2575          | 0.2525          | 0.6675          | 0.77            | 0.7625          |
| No log        | 28.98 | 483  | 1.1799          | 0.7675   | 0.245           | 0.2675          | 0.6725          | 0.765           | 0.765           |
| 0.5532        | 30.0  | 500  | 1.1495          | 0.775    | 0.2675          | 0.26            | 0.6675          | 0.7725          | 0.7775          |
| 0.5532        | 30.96 | 516  | 1.1995          | 0.7625   | 0.2675          | 0.315           | 0.6675          | 0.775           | 0.765           |
| 0.5532        | 31.98 | 533  | 1.2153          | 0.7575   | 0.2725          | 0.3325          | 0.6875          | 0.76            | 0.76            |
| 0.5532        | 33.0  | 550  | 1.2288          | 0.7725   | 0.27            | 0.35            | 0.6875          | 0.765           | 0.7625          |
| 0.5532        | 33.96 | 566  | 1.2132          | 0.7575   | 0.28            | 0.36            | 0.705           | 0.7475          | 0.7575          |
| 0.5532        | 34.98 | 583  | 1.1736          | 0.7725   | 0.2625          | 0.4075          | 0.72            | 0.77            | 0.77            |
| 0.5532        | 36.0  | 600  | 1.2199          | 0.775    | 0.2775          | 0.43            | 0.7125          | 0.7725          | 0.7775          |
| 0.5532        | 36.96 | 616  | 1.2147          | 0.7725   | 0.2825          | 0.435           | 0.71            | 0.78            | 0.7725          |
| 0.5532        | 37.98 | 633  | 1.2143          | 0.7725   | 0.275           | 0.45            | 0.72            | 0.78            | 0.77            |
| 0.5532        | 39.0  | 650  | 1.2248          | 0.77     | 0.275           | 0.4625          | 0.7025          | 0.7675          | 0.7675          |
| 0.5532        | 39.96 | 666  | 1.2268          | 0.765    | 0.2725          | 0.46            | 0.7225          | 0.77            | 0.7725          |
| 0.5532        | 40.98 | 683  | 1.1856          | 0.765    | 0.2725          | 0.485           | 0.725           | 0.7725          | 0.7625          |
| 0.5532        | 42.0  | 700  | 1.2291          | 0.76     | 0.275           | 0.485           | 0.71            | 0.755           | 0.755           |
| 0.5532        | 42.96 | 716  | 1.2208          | 0.7675   | 0.2725          | 0.4925          | 0.7025          | 0.7575          | 0.76            |
| 0.5532        | 43.98 | 733  | 1.2242          | 0.775    | 0.2825          | 0.5             | 0.7125          | 0.765           | 0.7625          |
| 0.5532        | 45.0  | 750  | 1.2462          | 0.7725   | 0.29            | 0.5             | 0.7075          | 0.765           | 0.77            |
| 0.5532        | 45.96 | 766  | 1.2655          | 0.7625   | 0.2875          | 0.5             | 0.705           | 0.7625          | 0.765           |
| 0.5532        | 46.98 | 783  | 1.2634          | 0.775    | 0.2875          | 0.505           | 0.715           | 0.755           | 0.7725          |
| 0.5532        | 48.0  | 800  | 1.2694          | 0.765    | 0.2875          | 0.51            | 0.7125          | 0.7575          | 0.765           |
| 0.5532        | 48.96 | 816  | 1.2824          | 0.7675   | 0.2875          | 0.5025          | 0.71            | 0.76            | 0.7725          |
| 0.5532        | 49.98 | 833  | 1.2705          | 0.765    | 0.2825          | 0.51            | 0.7175          | 0.76            | 0.7675          |
| 0.5532        | 51.0  | 850  | 1.2840          | 0.7625   | 0.285           | 0.505           | 0.715           | 0.7525          | 0.7625          |
| 0.5532        | 51.96 | 866  | 1.3022          | 0.7675   | 0.2875          | 0.5             | 0.7075          | 0.75            | 0.7675          |
| 0.5532        | 52.98 | 883  | 1.2999          | 0.765    | 0.2825          | 0.5             | 0.71            | 0.765           | 0.765           |
| 0.5532        | 54.0  | 900  | 1.3070          | 0.7675   | 0.2875          | 0.5025          | 0.71            | 0.7575          | 0.7675          |
| 0.5532        | 54.96 | 916  | 1.3163          | 0.7675   | 0.285           | 0.505           | 0.7125          | 0.755           | 0.765           |
| 0.5532        | 55.98 | 933  | 1.3197          | 0.7675   | 0.285           | 0.505           | 0.715           | 0.755           | 0.765           |
| 0.5532        | 57.0  | 950  | 1.3191          | 0.77     | 0.2825          | 0.5075          | 0.7125          | 0.7525          | 0.7625          |
| 0.5532        | 57.6  | 960  | 1.3189          | 0.7675   | 0.2825          | 0.5075          | 0.7125          | 0.7525          | 0.7625          |


### 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": "2024-01-10_one_stage_subgraphs_weighted_txt_vis_conc_2_5_9_11_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