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EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-09-03_txt_vis_concat_enc_12_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: 1.1463
- Accuracy: 0.805
- Exit 0 Accuracy: 0.08
- Exit 1 Accuracy: 0.8075
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 | 2.6926 | 0.115 | 0.03 | 0.0975 |
No log | 1.98 | 33 | 2.5577 | 0.22 | 0.06 | 0.1975 |
No log | 3.0 | 50 | 2.3770 | 0.305 | 0.065 | 0.305 |
No log | 3.96 | 66 | 2.1060 | 0.43 | 0.0675 | 0.43 |
No log | 4.98 | 83 | 1.8310 | 0.5775 | 0.065 | 0.5275 |
No log | 6.0 | 100 | 1.6004 | 0.615 | 0.065 | 0.595 |
No log | 6.96 | 116 | 1.3907 | 0.6925 | 0.065 | 0.6375 |
No log | 7.98 | 133 | 1.2449 | 0.71 | 0.065 | 0.71 |
No log | 9.0 | 150 | 1.1319 | 0.74 | 0.0675 | 0.7325 |
No log | 9.96 | 166 | 0.9893 | 0.7575 | 0.065 | 0.75 |
No log | 10.98 | 183 | 0.9431 | 0.7575 | 0.0675 | 0.7475 |
No log | 12.0 | 200 | 0.8968 | 0.76 | 0.0675 | 0.7575 |
No log | 12.96 | 216 | 0.8665 | 0.7725 | 0.065 | 0.765 |
No log | 13.98 | 233 | 0.9219 | 0.735 | 0.0675 | 0.745 |
No log | 15.0 | 250 | 0.8944 | 0.7475 | 0.065 | 0.755 |
No log | 15.96 | 266 | 0.8463 | 0.79 | 0.075 | 0.7825 |
No log | 16.98 | 283 | 0.9329 | 0.75 | 0.07 | 0.7475 |
No log | 18.0 | 300 | 0.9706 | 0.76 | 0.065 | 0.76 |
No log | 18.96 | 316 | 1.0194 | 0.745 | 0.065 | 0.75 |
No log | 19.98 | 333 | 0.9081 | 0.785 | 0.07 | 0.79 |
No log | 21.0 | 350 | 0.9894 | 0.785 | 0.075 | 0.7775 |
No log | 21.96 | 366 | 1.0477 | 0.74 | 0.075 | 0.7425 |
No log | 22.98 | 383 | 0.9729 | 0.7825 | 0.075 | 0.7825 |
No log | 24.0 | 400 | 1.0044 | 0.79 | 0.08 | 0.7925 |
No log | 24.96 | 416 | 1.0300 | 0.78 | 0.08 | 0.7875 |
No log | 25.98 | 433 | 0.9863 | 0.7975 | 0.0775 | 0.7975 |
No log | 27.0 | 450 | 0.9913 | 0.7975 | 0.075 | 0.8 |
No log | 27.96 | 466 | 1.0085 | 0.8 | 0.0775 | 0.8025 |
No log | 28.98 | 483 | 1.0336 | 0.8 | 0.0775 | 0.8025 |
1.2663 | 30.0 | 500 | 1.0423 | 0.7925 | 0.08 | 0.8 |
1.2663 | 30.96 | 516 | 1.0509 | 0.7925 | 0.0775 | 0.8025 |
1.2663 | 31.98 | 533 | 1.0561 | 0.7925 | 0.08 | 0.795 |
1.2663 | 33.0 | 550 | 1.0546 | 0.8 | 0.08 | 0.8 |
1.2663 | 33.96 | 566 | 1.0632 | 0.8 | 0.08 | 0.8 |
1.2663 | 34.98 | 583 | 1.0605 | 0.805 | 0.075 | 0.81 |
1.2663 | 36.0 | 600 | 1.1232 | 0.795 | 0.0775 | 0.7975 |
1.2663 | 36.96 | 616 | 1.0872 | 0.805 | 0.0775 | 0.8025 |
1.2663 | 37.98 | 633 | 1.0939 | 0.81 | 0.0775 | 0.81 |
1.2663 | 39.0 | 650 | 1.0951 | 0.8125 | 0.0775 | 0.81 |
1.2663 | 39.96 | 666 | 1.1014 | 0.81 | 0.08 | 0.81 |
1.2663 | 40.98 | 683 | 1.1039 | 0.81 | 0.08 | 0.81 |
1.2663 | 42.0 | 700 | 1.1108 | 0.81 | 0.08 | 0.8075 |
1.2663 | 42.96 | 716 | 1.1139 | 0.81 | 0.08 | 0.8125 |
1.2663 | 43.98 | 733 | 1.1177 | 0.81 | 0.08 | 0.8125 |
1.2663 | 45.0 | 750 | 1.1245 | 0.8075 | 0.08 | 0.81 |
1.2663 | 45.96 | 766 | 1.1309 | 0.8075 | 0.08 | 0.8075 |
1.2663 | 46.98 | 783 | 1.1336 | 0.805 | 0.08 | 0.8075 |
1.2663 | 48.0 | 800 | 1.1336 | 0.8075 | 0.08 | 0.8075 |
1.2663 | 48.96 | 816 | 1.1368 | 0.8075 | 0.08 | 0.8075 |
1.2663 | 49.98 | 833 | 1.1348 | 0.805 | 0.08 | 0.8075 |
1.2663 | 51.0 | 850 | 1.1389 | 0.805 | 0.08 | 0.805 |
1.2663 | 51.96 | 866 | 1.1414 | 0.805 | 0.08 | 0.805 |
1.2663 | 52.98 | 883 | 1.1422 | 0.805 | 0.08 | 0.805 |
1.2663 | 54.0 | 900 | 1.1435 | 0.805 | 0.08 | 0.8075 |
1.2663 | 54.96 | 916 | 1.1442 | 0.805 | 0.08 | 0.8075 |
1.2663 | 55.98 | 933 | 1.1461 | 0.805 | 0.08 | 0.8075 |
1.2663 | 57.0 | 950 | 1.1462 | 0.805 | 0.08 | 0.8075 |
1.2663 | 57.6 | 960 | 1.1463 | 0.805 | 0.08 | 0.8075 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3