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# EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-12-05_txt_vis_concat_enc_9_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: 0.9836
- Accuracy: 0.755
- Exit 0 Accuracy: 0.055
- Exit 1 Accuracy: 0.0625

## 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    | 2.7543          | 0.09     | 0.04            | 0.0625          |
| No log        | 1.96  | 8    | 2.7090          | 0.15     | 0.045           | 0.0625          |
| No log        | 2.96  | 12   | 2.6189          | 0.185    | 0.0475          | 0.0625          |
| No log        | 3.96  | 16   | 2.5508          | 0.2025   | 0.0525          | 0.0625          |
| No log        | 4.96  | 20   | 2.4955          | 0.2125   | 0.05            | 0.0625          |
| No log        | 5.96  | 24   | 2.3794          | 0.275    | 0.05            | 0.0625          |
| No log        | 6.96  | 28   | 2.2952          | 0.3225   | 0.0525          | 0.0625          |
| No log        | 7.96  | 32   | 2.1989          | 0.3575   | 0.0525          | 0.0625          |
| No log        | 8.96  | 36   | 2.1110          | 0.375    | 0.055           | 0.0625          |
| No log        | 9.96  | 40   | 2.0165          | 0.41     | 0.055           | 0.0625          |
| No log        | 10.96 | 44   | 1.9297          | 0.4325   | 0.055           | 0.0625          |
| No log        | 11.96 | 48   | 1.8067          | 0.4925   | 0.055           | 0.0625          |
| No log        | 12.96 | 52   | 1.6998          | 0.555    | 0.055           | 0.0625          |
| No log        | 13.96 | 56   | 1.6331          | 0.5175   | 0.055           | 0.0625          |
| No log        | 14.96 | 60   | 1.5114          | 0.5825   | 0.055           | 0.0625          |
| No log        | 15.96 | 64   | 1.4501          | 0.615    | 0.0575          | 0.0625          |
| No log        | 16.96 | 68   | 1.3538          | 0.62     | 0.0575          | 0.0625          |
| No log        | 17.96 | 72   | 1.2836          | 0.6525   | 0.0575          | 0.0625          |
| No log        | 18.96 | 76   | 1.2582          | 0.65     | 0.0575          | 0.0625          |
| No log        | 19.96 | 80   | 1.1753          | 0.6625   | 0.0575          | 0.065           |
| No log        | 20.96 | 84   | 1.1471          | 0.695    | 0.0575          | 0.0725          |
| No log        | 21.96 | 88   | 1.1038          | 0.7025   | 0.0575          | 0.0875          |
| No log        | 22.96 | 92   | 1.0410          | 0.73     | 0.0575          | 0.08            |
| No log        | 23.96 | 96   | 1.0374          | 0.7325   | 0.0575          | 0.07            |
| No log        | 24.96 | 100  | 1.0223          | 0.7325   | 0.0575          | 0.0675          |
| No log        | 25.96 | 104  | 1.0262          | 0.73     | 0.06            | 0.065           |
| No log        | 26.96 | 108  | 0.9950          | 0.715    | 0.06            | 0.065           |
| No log        | 27.96 | 112  | 0.9828          | 0.7325   | 0.06            | 0.0625          |
| No log        | 28.96 | 116  | 0.9560          | 0.7325   | 0.06            | 0.0625          |
| No log        | 29.96 | 120  | 0.9717          | 0.7325   | 0.06            | 0.0625          |
| No log        | 30.96 | 124  | 0.9441          | 0.73     | 0.06            | 0.0625          |
| No log        | 31.96 | 128  | 0.9550          | 0.7375   | 0.06            | 0.0625          |
| No log        | 32.96 | 132  | 0.9510          | 0.7375   | 0.06            | 0.0625          |
| No log        | 33.96 | 136  | 0.9451          | 0.735    | 0.06            | 0.0625          |
| No log        | 34.96 | 140  | 0.9486          | 0.7475   | 0.06            | 0.0625          |
| No log        | 35.96 | 144  | 0.9575          | 0.75     | 0.0575          | 0.0625          |
| No log        | 36.96 | 148  | 0.9427          | 0.73     | 0.0575          | 0.0625          |
| No log        | 37.96 | 152  | 0.9728          | 0.75     | 0.0575          | 0.0625          |
| No log        | 38.96 | 156  | 0.9450          | 0.7375   | 0.06            | 0.0625          |
| No log        | 39.96 | 160  | 0.9645          | 0.755    | 0.0575          | 0.0625          |
| No log        | 40.96 | 164  | 0.9655          | 0.75     | 0.055           | 0.0625          |
| No log        | 41.96 | 168  | 0.9582          | 0.745    | 0.055           | 0.0625          |
| No log        | 42.96 | 172  | 0.9721          | 0.7475   | 0.055           | 0.0625          |
| No log        | 43.96 | 176  | 0.9720          | 0.7475   | 0.055           | 0.0625          |
| No log        | 44.96 | 180  | 0.9703          | 0.75     | 0.055           | 0.065           |
| No log        | 45.96 | 184  | 0.9781          | 0.7475   | 0.055           | 0.0625          |
| No log        | 46.96 | 188  | 0.9661          | 0.75     | 0.055           | 0.0625          |
| No log        | 47.96 | 192  | 0.9671          | 0.75     | 0.055           | 0.0625          |
| No log        | 48.96 | 196  | 0.9767          | 0.75     | 0.055           | 0.0625          |
| No log        | 49.96 | 200  | 0.9646          | 0.7525   | 0.055           | 0.0625          |
| No log        | 50.96 | 204  | 0.9788          | 0.7525   | 0.055           | 0.0625          |
| No log        | 51.96 | 208  | 0.9904          | 0.755    | 0.055           | 0.0625          |
| No log        | 52.96 | 212  | 0.9857          | 0.7575   | 0.055           | 0.0625          |
| No log        | 53.96 | 216  | 0.9756          | 0.7525   | 0.055           | 0.065           |
| No log        | 54.96 | 220  | 0.9758          | 0.7525   | 0.055           | 0.0625          |
| No log        | 55.96 | 224  | 0.9774          | 0.755    | 0.055           | 0.0625          |
| No log        | 56.96 | 228  | 0.9785          | 0.755    | 0.055           | 0.0625          |
| No log        | 57.96 | 232  | 0.9817          | 0.7525   | 0.055           | 0.0625          |
| No log        | 58.96 | 236  | 0.9833          | 0.755    | 0.055           | 0.0625          |
| No log        | 59.96 | 240  | 0.9836          | 0.755    | 0.055           | 0.0625          |


### 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": "EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-12-05_txt_vis_concat_enc_9_gate", "results": []}]}
transformers pytorch layoutlmv3 text-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us