<!-- 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. -->
EElayoutlmv3_jordyvl_rvl_cdip_100_examples_per_class_2023-09-02_txt_vis_concat_enc_8_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: 1.3797
- Accuracy: 0.7775
- Exit 0 Accuracy: 0.0975
- Exit 1 Accuracy: 0.7825
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 | 2.6923 | 0.125 | 0.0425 | 0.0625 |
No log | 1.98 | 33 | 2.5475 | 0.215 | 0.0675 | 0.0625 |
No log | 3.0 | 50 | 2.4085 | 0.2725 | 0.075 | 0.0625 |
No log | 3.96 | 66 | 2.1946 | 0.365 | 0.0775 | 0.0625 |
No log | 4.98 | 83 | 1.9525 | 0.5 | 0.08 | 0.0625 |
No log | 6.0 | 100 | 1.6874 | 0.5775 | 0.08 | 0.0625 |
No log | 6.96 | 116 | 1.4652 | 0.6475 | 0.0825 | 0.0625 |
No log | 7.98 | 133 | 1.3144 | 0.67 | 0.0825 | 0.0625 |
No log | 9.0 | 150 | 1.1765 | 0.71 | 0.0825 | 0.0625 |
No log | 9.96 | 166 | 1.0615 | 0.7325 | 0.085 | 0.0625 |
No log | 10.98 | 183 | 1.0225 | 0.7425 | 0.085 | 0.0625 |
No log | 12.0 | 200 | 0.9310 | 0.7775 | 0.085 | 0.09 |
No log | 12.96 | 216 | 0.9445 | 0.7475 | 0.0875 | 0.25 |
No log | 13.98 | 233 | 0.9819 | 0.74 | 0.085 | 0.5325 |
No log | 15.0 | 250 | 0.9187 | 0.755 | 0.085 | 0.6775 |
No log | 15.96 | 266 | 0.9655 | 0.75 | 0.09 | 0.705 |
No log | 16.98 | 283 | 1.0417 | 0.7525 | 0.08 | 0.7125 |
No log | 18.0 | 300 | 0.9947 | 0.7675 | 0.08 | 0.7325 |
No log | 18.96 | 316 | 1.0721 | 0.7475 | 0.085 | 0.725 |
No log | 19.98 | 333 | 1.0403 | 0.765 | 0.0825 | 0.74 |
No log | 21.0 | 350 | 1.0728 | 0.76 | 0.085 | 0.7475 |
No log | 21.96 | 366 | 1.1415 | 0.75 | 0.09 | 0.745 |
No log | 22.98 | 383 | 1.0932 | 0.765 | 0.09 | 0.7775 |
No log | 24.0 | 400 | 1.1408 | 0.77 | 0.095 | 0.775 |
No log | 24.96 | 416 | 1.1579 | 0.775 | 0.0975 | 0.7675 |
No log | 25.98 | 433 | 1.1688 | 0.7725 | 0.0925 | 0.78 |
No log | 27.0 | 450 | 1.1945 | 0.7675 | 0.09 | 0.77 |
No log | 27.96 | 466 | 1.1929 | 0.7675 | 0.09 | 0.7775 |
No log | 28.98 | 483 | 1.2495 | 0.77 | 0.0925 | 0.775 |
1.457 | 30.0 | 500 | 1.1974 | 0.7775 | 0.0975 | 0.79 |
1.457 | 30.96 | 516 | 1.2452 | 0.7725 | 0.09 | 0.785 |
1.457 | 31.98 | 533 | 1.2672 | 0.7775 | 0.095 | 0.7825 |
1.457 | 33.0 | 550 | 1.2877 | 0.7725 | 0.095 | 0.78 |
1.457 | 33.96 | 566 | 1.2928 | 0.7775 | 0.0975 | 0.785 |
1.457 | 34.98 | 583 | 1.2982 | 0.775 | 0.095 | 0.7825 |
1.457 | 36.0 | 600 | 1.3094 | 0.775 | 0.095 | 0.7875 |
1.457 | 36.96 | 616 | 1.3342 | 0.77 | 0.095 | 0.78 |
1.457 | 37.98 | 633 | 1.3218 | 0.77 | 0.0925 | 0.7825 |
1.457 | 39.0 | 650 | 1.3302 | 0.77 | 0.095 | 0.79 |
1.457 | 39.96 | 666 | 1.3409 | 0.7725 | 0.095 | 0.7825 |
1.457 | 40.98 | 683 | 1.3496 | 0.7725 | 0.0975 | 0.7825 |
1.457 | 42.0 | 700 | 1.3411 | 0.7775 | 0.095 | 0.7825 |
1.457 | 42.96 | 716 | 1.3441 | 0.775 | 0.0975 | 0.785 |
1.457 | 43.98 | 733 | 1.3500 | 0.775 | 0.095 | 0.785 |
1.457 | 45.0 | 750 | 1.3569 | 0.775 | 0.095 | 0.785 |
1.457 | 45.96 | 766 | 1.3555 | 0.775 | 0.0975 | 0.7875 |
1.457 | 46.98 | 783 | 1.3589 | 0.775 | 0.0975 | 0.7825 |
1.457 | 48.0 | 800 | 1.3597 | 0.7725 | 0.0925 | 0.78 |
1.457 | 48.96 | 816 | 1.3666 | 0.7725 | 0.0975 | 0.785 |
1.457 | 49.98 | 833 | 1.3718 | 0.7675 | 0.095 | 0.7825 |
1.457 | 51.0 | 850 | 1.3767 | 0.7725 | 0.0975 | 0.785 |
1.457 | 51.96 | 866 | 1.3846 | 0.775 | 0.0975 | 0.7825 |
1.457 | 52.98 | 883 | 1.3835 | 0.775 | 0.0975 | 0.7825 |
1.457 | 54.0 | 900 | 1.3832 | 0.775 | 0.0975 | 0.785 |
1.457 | 54.96 | 916 | 1.3807 | 0.775 | 0.0975 | 0.785 |
1.457 | 55.98 | 933 | 1.3793 | 0.7775 | 0.0975 | 0.785 |
1.457 | 57.0 | 950 | 1.3796 | 0.7775 | 0.0975 | 0.7825 |
1.457 | 57.6 | 960 | 1.3797 | 0.7775 | 0.0975 | 0.7825 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3