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EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-08-30_txt_vis_concat_enc_1_ramp
This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3611
- Accuracy: 0.755
- Exit 0 Accuracy: 0.0925
- Exit 1 Accuracy: 0.545
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 | 2.7004 | 0.125 | 0.045 | 0.0625 |
| No log | 1.98 | 33 | 2.5536 | 0.2275 | 0.0475 | 0.0575 |
| No log | 3.0 | 50 | 2.3739 | 0.3225 | 0.055 | 0.0675 |
| No log | 3.96 | 66 | 2.1714 | 0.3975 | 0.0625 | 0.1325 |
| No log | 4.98 | 83 | 1.9722 | 0.46 | 0.0675 | 0.135 |
| No log | 6.0 | 100 | 1.7050 | 0.5625 | 0.07 | 0.1225 |
| No log | 6.96 | 116 | 1.4837 | 0.62 | 0.085 | 0.1925 |
| No log | 7.98 | 133 | 1.3380 | 0.675 | 0.0825 | 0.2175 |
| No log | 9.0 | 150 | 1.2165 | 0.6775 | 0.09 | 0.2675 |
| No log | 9.96 | 166 | 1.1170 | 0.695 | 0.09 | 0.335 |
| No log | 10.98 | 183 | 1.0124 | 0.73 | 0.095 | 0.34 |
| No log | 12.0 | 200 | 0.9469 | 0.75 | 0.0925 | 0.36 |
| No log | 12.96 | 216 | 0.9763 | 0.715 | 0.0975 | 0.385 |
| No log | 13.98 | 233 | 0.9486 | 0.7425 | 0.09 | 0.41 |
| No log | 15.0 | 250 | 0.9872 | 0.725 | 0.0925 | 0.405 |
| No log | 15.96 | 266 | 0.9373 | 0.745 | 0.0925 | 0.4225 |
| No log | 16.98 | 283 | 0.9517 | 0.75 | 0.085 | 0.4025 |
| No log | 18.0 | 300 | 0.9673 | 0.745 | 0.08 | 0.4475 |
| No log | 18.96 | 316 | 1.0213 | 0.7425 | 0.0825 | 0.4525 |
| No log | 19.98 | 333 | 1.0320 | 0.75 | 0.085 | 0.44 |
| No log | 21.0 | 350 | 1.0484 | 0.76 | 0.09 | 0.4575 |
| No log | 21.96 | 366 | 1.0196 | 0.765 | 0.0875 | 0.47 |
| No log | 22.98 | 383 | 1.0498 | 0.75 | 0.085 | 0.45 |
| No log | 24.0 | 400 | 1.1435 | 0.74 | 0.0875 | 0.4775 |
| No log | 24.96 | 416 | 1.0839 | 0.7725 | 0.0875 | 0.4725 |
| No log | 25.98 | 433 | 1.1052 | 0.76 | 0.09 | 0.475 |
| No log | 27.0 | 450 | 1.1310 | 0.765 | 0.09 | 0.485 |
| No log | 27.96 | 466 | 1.1441 | 0.7775 | 0.09 | 0.4775 |
| No log | 28.98 | 483 | 1.1635 | 0.77 | 0.09 | 0.475 |
| 1.6676 | 30.0 | 500 | 1.2218 | 0.75 | 0.085 | 0.4825 |
| 1.6676 | 30.96 | 516 | 1.2521 | 0.76 | 0.09 | 0.495 |
| 1.6676 | 31.98 | 533 | 1.2850 | 0.7425 | 0.09 | 0.495 |
| 1.6676 | 33.0 | 550 | 1.2516 | 0.76 | 0.09 | 0.4975 |
| 1.6676 | 33.96 | 566 | 1.3101 | 0.7575 | 0.09 | 0.4975 |
| 1.6676 | 34.98 | 583 | 1.2974 | 0.765 | 0.09 | 0.5 |
| 1.6676 | 36.0 | 600 | 1.2978 | 0.7575 | 0.0925 | 0.5025 |
| 1.6676 | 36.96 | 616 | 1.2925 | 0.76 | 0.09 | 0.51 |
| 1.6676 | 37.98 | 633 | 1.3120 | 0.7625 | 0.0925 | 0.5125 |
| 1.6676 | 39.0 | 650 | 1.3167 | 0.7575 | 0.09 | 0.5125 |
| 1.6676 | 39.96 | 666 | 1.3262 | 0.7525 | 0.09 | 0.5175 |
| 1.6676 | 40.98 | 683 | 1.3281 | 0.7475 | 0.0925 | 0.5225 |
| 1.6676 | 42.0 | 700 | 1.3403 | 0.75 | 0.0925 | 0.5125 |
| 1.6676 | 42.96 | 716 | 1.3291 | 0.745 | 0.0925 | 0.5175 |
| 1.6676 | 43.98 | 733 | 1.3549 | 0.76 | 0.0925 | 0.515 |
| 1.6676 | 45.0 | 750 | 1.3520 | 0.7525 | 0.0925 | 0.5275 |
| 1.6676 | 45.96 | 766 | 1.3458 | 0.745 | 0.0925 | 0.525 |
| 1.6676 | 46.98 | 783 | 1.3457 | 0.7425 | 0.0925 | 0.535 |
| 1.6676 | 48.0 | 800 | 1.3441 | 0.7525 | 0.0925 | 0.5425 |
| 1.6676 | 48.96 | 816 | 1.3477 | 0.755 | 0.0925 | 0.5325 |
| 1.6676 | 49.98 | 833 | 1.3557 | 0.7575 | 0.0925 | 0.54 |
| 1.6676 | 51.0 | 850 | 1.3631 | 0.755 | 0.0925 | 0.54 |
| 1.6676 | 51.96 | 866 | 1.3643 | 0.7525 | 0.0925 | 0.5375 |
| 1.6676 | 52.98 | 883 | 1.3590 | 0.755 | 0.0925 | 0.5425 |
| 1.6676 | 54.0 | 900 | 1.3604 | 0.755 | 0.0925 | 0.5475 |
| 1.6676 | 54.96 | 916 | 1.3607 | 0.755 | 0.0925 | 0.5475 |
| 1.6676 | 55.98 | 933 | 1.3609 | 0.7525 | 0.0925 | 0.54 |
| 1.6676 | 57.0 | 950 | 1.3610 | 0.755 | 0.0925 | 0.545 |
| 1.6676 | 57.6 | 960 | 1.3611 | 0.755 | 0.0925 | 0.545 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
