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EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-05-17_gofor50
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: 1.4441
- Accuracy: 0.7
- Exit 0 Accuracy: 0.15
- Exit 1 Accuracy: 0.1775
- Exit 2 Accuracy: 0.515
- Exit 3 Accuracy: 0.705
- Exit 4 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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
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 | 12 | 2.6817 | 0.1475 | 0.0825 | 0.0525 | 0.1225 | 0.0625 | 0.0625 |
No log | 2.0 | 25 | 2.5448 | 0.235 | 0.0875 | 0.1125 | 0.0875 | 0.12 | 0.0625 |
No log | 2.96 | 37 | 2.3948 | 0.2825 | 0.105 | 0.14 | 0.205 | 0.21 | 0.0625 |
No log | 4.0 | 50 | 2.4502 | 0.3125 | 0.1125 | 0.1425 | 0.2 | 0.1725 | 0.22 |
No log | 4.96 | 62 | 2.1482 | 0.385 | 0.11 | 0.145 | 0.2925 | 0.3275 | 0.275 |
No log | 6.0 | 75 | 1.8840 | 0.465 | 0.1175 | 0.1475 | 0.33 | 0.4075 | 0.4925 |
No log | 6.96 | 87 | 1.6813 | 0.5725 | 0.1225 | 0.16 | 0.3475 | 0.4475 | 0.55 |
No log | 8.0 | 100 | 1.5199 | 0.605 | 0.13 | 0.1575 | 0.3375 | 0.5 | 0.585 |
No log | 8.96 | 112 | 1.4031 | 0.6125 | 0.1325 | 0.1575 | 0.365 | 0.5325 | 0.6025 |
No log | 10.0 | 125 | 1.3312 | 0.62 | 0.13 | 0.1575 | 0.3825 | 0.565 | 0.62 |
No log | 10.96 | 137 | 1.2133 | 0.6575 | 0.1175 | 0.1575 | 0.385 | 0.605 | 0.6275 |
No log | 12.0 | 150 | 1.1805 | 0.68 | 0.135 | 0.1675 | 0.38 | 0.6225 | 0.645 |
No log | 12.96 | 162 | 1.1987 | 0.6625 | 0.12 | 0.165 | 0.4075 | 0.63 | 0.645 |
No log | 14.0 | 175 | 1.1304 | 0.6975 | 0.12 | 0.17 | 0.41 | 0.6375 | 0.6725 |
No log | 14.96 | 187 | 1.1333 | 0.695 | 0.125 | 0.1675 | 0.42 | 0.655 | 0.675 |
No log | 16.0 | 200 | 1.1373 | 0.6975 | 0.1425 | 0.1725 | 0.4375 | 0.655 | 0.6825 |
No log | 16.96 | 212 | 1.0988 | 0.7125 | 0.1475 | 0.165 | 0.44 | 0.66 | 0.6975 |
No log | 18.0 | 225 | 1.1830 | 0.7 | 0.125 | 0.165 | 0.455 | 0.675 | 0.69 |
No log | 18.96 | 237 | 1.1827 | 0.685 | 0.13 | 0.1575 | 0.45 | 0.665 | 0.6825 |
No log | 20.0 | 250 | 1.2335 | 0.695 | 0.125 | 0.1575 | 0.455 | 0.6675 | 0.685 |
No log | 20.96 | 262 | 1.2793 | 0.6625 | 0.135 | 0.1575 | 0.4475 | 0.665 | 0.6775 |
No log | 22.0 | 275 | 1.2136 | 0.71 | 0.14 | 0.155 | 0.4675 | 0.6775 | 0.6925 |
No log | 22.96 | 287 | 1.1790 | 0.7025 | 0.135 | 0.16 | 0.4725 | 0.6725 | 0.6975 |
No log | 24.0 | 300 | 1.2636 | 0.6825 | 0.125 | 0.1625 | 0.4375 | 0.6675 | 0.6825 |
No log | 24.96 | 312 | 1.2949 | 0.6775 | 0.1225 | 0.165 | 0.46 | 0.6625 | 0.685 |
No log | 26.0 | 325 | 1.2979 | 0.685 | 0.135 | 0.1625 | 0.455 | 0.69 | 0.6925 |
No log | 26.96 | 337 | 1.3059 | 0.6825 | 0.1375 | 0.1675 | 0.475 | 0.675 | 0.69 |
No log | 28.0 | 350 | 1.3239 | 0.6975 | 0.1375 | 0.17 | 0.4725 | 0.68 | 0.705 |
No log | 28.96 | 362 | 1.3181 | 0.7 | 0.1325 | 0.1725 | 0.465 | 0.6725 | 0.695 |
No log | 30.0 | 375 | 1.3978 | 0.68 | 0.1375 | 0.1675 | 0.4825 | 0.6825 | 0.68 |
No log | 30.96 | 387 | 1.2876 | 0.715 | 0.14 | 0.175 | 0.49 | 0.6925 | 0.7125 |
No log | 32.0 | 400 | 1.3233 | 0.6975 | 0.1475 | 0.1725 | 0.4875 | 0.6975 | 0.705 |
No log | 32.96 | 412 | 1.3607 | 0.7 | 0.135 | 0.1725 | 0.4925 | 0.6925 | 0.7075 |
No log | 34.0 | 425 | 1.3728 | 0.6925 | 0.1525 | 0.1725 | 0.4925 | 0.685 | 0.7025 |
No log | 34.96 | 437 | 1.3931 | 0.695 | 0.1425 | 0.1725 | 0.49 | 0.695 | 0.7 |
No log | 36.0 | 450 | 1.3642 | 0.7125 | 0.145 | 0.1725 | 0.505 | 0.6875 | 0.71 |
No log | 36.96 | 462 | 1.3807 | 0.705 | 0.1475 | 0.17 | 0.4975 | 0.6875 | 0.695 |
No log | 38.0 | 475 | 1.4171 | 0.7025 | 0.1575 | 0.17 | 0.505 | 0.6975 | 0.695 |
No log | 38.96 | 487 | 1.3868 | 0.71 | 0.155 | 0.17 | 0.4975 | 0.7025 | 0.705 |
0.6814 | 40.0 | 500 | 1.3982 | 0.7075 | 0.1425 | 0.17 | 0.51 | 0.6975 | 0.705 |
0.6814 | 40.96 | 512 | 1.3898 | 0.7075 | 0.1475 | 0.17 | 0.51 | 0.6975 | 0.6975 |
0.6814 | 42.0 | 525 | 1.4277 | 0.7025 | 0.145 | 0.17 | 0.515 | 0.705 | 0.705 |
0.6814 | 42.96 | 537 | 1.4381 | 0.7025 | 0.145 | 0.1725 | 0.51 | 0.7 | 0.7025 |
0.6814 | 44.0 | 550 | 1.4374 | 0.7025 | 0.15 | 0.175 | 0.5125 | 0.7 | 0.7 |
0.6814 | 44.96 | 562 | 1.4260 | 0.6975 | 0.1475 | 0.175 | 0.5125 | 0.7025 | 0.7 |
0.6814 | 46.0 | 575 | 1.4408 | 0.7 | 0.1475 | 0.1775 | 0.5125 | 0.7025 | 0.7 |
0.6814 | 46.96 | 587 | 1.4483 | 0.7 | 0.15 | 0.1775 | 0.515 | 0.705 | 0.7 |
0.6814 | 48.0 | 600 | 1.4441 | 0.7 | 0.15 | 0.1775 | 0.515 | 0.705 | 0.7025 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.12.0
- Tokenizers 0.12.1