
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 2024-01-02_one_stage_subgraphs_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: 1.1266
- Accuracy: 0.705
- Exit 0 Accuracy: 0.195
- Exit 1 Accuracy: 0.7025

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 24
- total_train_batch_size: 192
- 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  | 4    | 2.7544          | 0.115    | 0.0575          | 0.0625          |
| No log        | 1.96  | 8    | 2.6911          | 0.135    | 0.125           | 0.0625          |
| No log        | 2.96  | 12   | 2.6410          | 0.1775   | 0.1225          | 0.18            |
| No log        | 3.96  | 16   | 2.5664          | 0.2025   | 0.125           | 0.1825          |
| No log        | 4.96  | 20   | 2.5036          | 0.2475   | 0.1225          | 0.2475          |
| No log        | 5.96  | 24   | 2.4172          | 0.28     | 0.12            | 0.2275          |
| No log        | 6.96  | 28   | 2.3247          | 0.3      | 0.1275          | 0.2225          |
| No log        | 7.96  | 32   | 2.2355          | 0.36     | 0.14            | 0.2525          |
| No log        | 8.96  | 36   | 2.1384          | 0.4025   | 0.1375          | 0.315           |
| No log        | 9.96  | 40   | 2.0150          | 0.465    | 0.14            | 0.3475          |
| No log        | 10.96 | 44   | 1.9193          | 0.4925   | 0.1425          | 0.37            |
| No log        | 11.96 | 48   | 1.7777          | 0.5375   | 0.145           | 0.4325          |
| No log        | 12.96 | 52   | 1.6960          | 0.56     | 0.15            | 0.5             |
| No log        | 13.96 | 56   | 1.5905          | 0.59     | 0.155           | 0.49            |
| No log        | 14.96 | 60   | 1.5197          | 0.625    | 0.155           | 0.5275          |
| No log        | 15.96 | 64   | 1.4335          | 0.6475   | 0.1525          | 0.5425          |
| No log        | 16.96 | 68   | 1.3831          | 0.6575   | 0.1575          | 0.5675          |
| No log        | 17.96 | 72   | 1.3216          | 0.6775   | 0.155           | 0.575           |
| No log        | 18.96 | 76   | 1.2973          | 0.6825   | 0.1575          | 0.5825          |
| No log        | 19.96 | 80   | 1.2342          | 0.6975   | 0.1575          | 0.6025          |
| No log        | 20.96 | 84   | 1.2190          | 0.6825   | 0.16            | 0.605           |
| No log        | 21.96 | 88   | 1.1758          | 0.7125   | 0.1625          | 0.62            |
| No log        | 22.96 | 92   | 1.1612          | 0.685    | 0.1675          | 0.625           |
| No log        | 23.96 | 96   | 1.1329          | 0.6925   | 0.1675          | 0.64            |
| No log        | 24.96 | 100  | 1.1001          | 0.7125   | 0.1675          | 0.635           |
| No log        | 25.96 | 104  | 1.0943          | 0.7025   | 0.175           | 0.645           |
| No log        | 26.96 | 108  | 1.0794          | 0.7125   | 0.18            | 0.6475          |
| No log        | 27.96 | 112  | 1.0919          | 0.6925   | 0.185           | 0.6475          |
| No log        | 28.96 | 116  | 1.0630          | 0.72     | 0.1875          | 0.6575          |
| No log        | 29.96 | 120  | 1.0831          | 0.7      | 0.1875          | 0.655           |
| No log        | 30.96 | 124  | 1.0581          | 0.695    | 0.1875          | 0.6625          |
| No log        | 31.96 | 128  | 1.0588          | 0.715    | 0.1875          | 0.66            |
| No log        | 32.96 | 132  | 1.0624          | 0.6975   | 0.185           | 0.675           |
| No log        | 33.96 | 136  | 1.0355          | 0.71     | 0.1875          | 0.675           |
| No log        | 34.96 | 140  | 1.0777          | 0.6925   | 0.1875          | 0.665           |
| No log        | 35.96 | 144  | 1.0514          | 0.71     | 0.19            | 0.675           |
| No log        | 36.96 | 148  | 1.0678          | 0.7      | 0.1925          | 0.6825          |
| No log        | 37.96 | 152  | 1.0610          | 0.7025   | 0.1925          | 0.68            |
| No log        | 38.96 | 156  | 1.0726          | 0.7025   | 0.195           | 0.69            |
| No log        | 39.96 | 160  | 1.0818          | 0.7025   | 0.195           | 0.69            |
| No log        | 40.96 | 164  | 1.0893          | 0.6975   | 0.1925          | 0.685           |
| No log        | 41.96 | 168  | 1.0980          | 0.695    | 0.195           | 0.69            |
| No log        | 42.96 | 172  | 1.1009          | 0.7025   | 0.1925          | 0.6925          |
| No log        | 43.96 | 176  | 1.0896          | 0.705    | 0.1925          | 0.695           |
| No log        | 44.96 | 180  | 1.0697          | 0.7125   | 0.1925          | 0.695           |
| No log        | 45.96 | 184  | 1.1185          | 0.7025   | 0.1925          | 0.695           |
| No log        | 46.96 | 188  | 1.0956          | 0.705    | 0.1925          | 0.6925          |
| No log        | 47.96 | 192  | 1.1095          | 0.71     | 0.19            | 0.6975          |
| No log        | 48.96 | 196  | 1.1233          | 0.7075   | 0.1925          | 0.7025          |
| No log        | 49.96 | 200  | 1.1281          | 0.705    | 0.1925          | 0.7025          |
| No log        | 50.96 | 204  | 1.1428          | 0.6975   | 0.1925          | 0.7025          |
| No log        | 51.96 | 208  | 1.1292          | 0.7025   | 0.1925          | 0.71            |
| No log        | 52.96 | 212  | 1.1218          | 0.7025   | 0.19            | 0.7125          |
| No log        | 53.96 | 216  | 1.1143          | 0.7075   | 0.1925          | 0.7025          |
| No log        | 54.96 | 220  | 1.1192          | 0.7125   | 0.195           | 0.7025          |
| No log        | 55.96 | 224  | 1.1338          | 0.715    | 0.195           | 0.7025          |
| No log        | 56.96 | 228  | 1.1333          | 0.71     | 0.195           | 0.7075          |
| No log        | 57.96 | 232  | 1.1291          | 0.7025   | 0.195           | 0.7025          |
| No log        | 58.96 | 236  | 1.1268          | 0.705    | 0.195           | 0.705           |
| No log        | 59.96 | 240  | 1.1266          | 0.705    | 0.195           | 0.7025          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "2024-01-02_one_stage_subgraphs_entropyreg_txt_vis_conc_6_ramp", "results": []}]}
transformers pytorch layoutlmv3 text-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us