generated_from_trainer

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layoutlmv3-finetuned-wildreceipt

This model is a fine-tuned version of microsoft/layoutlmv3-base on the wildreceipt dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 0.32 100 1.3498 0.6130 0.3126 0.4140 0.6742
No log 0.63 200 0.8939 0.6665 0.5317 0.5915 0.7815
No log 0.95 300 0.7159 0.7311 0.6425 0.6840 0.8161
No log 1.26 400 0.5901 0.7554 0.6690 0.7095 0.8405
1.0677 1.58 500 0.5263 0.7632 0.7232 0.7427 0.8578
1.0677 1.89 600 0.4759 0.7871 0.7777 0.7824 0.8774
1.0677 2.21 700 0.4299 0.8054 0.8070 0.8062 0.8890
1.0677 2.52 800 0.4165 0.8064 0.8311 0.8185 0.8937
1.0677 2.84 900 0.3845 0.8344 0.8300 0.8322 0.9005
0.4267 3.15 1000 0.3540 0.8433 0.8318 0.8375 0.9056
0.4267 3.47 1100 0.3429 0.8362 0.8540 0.8450 0.9086
0.4267 3.79 1200 0.3274 0.8451 0.8545 0.8498 0.9105
0.4267 4.1 1300 0.3433 0.8397 0.8535 0.8466 0.9092
0.4267 4.42 1400 0.3181 0.8514 0.8604 0.8559 0.9154
0.2869 4.73 1500 0.3191 0.8472 0.8637 0.8554 0.9129
0.2869 5.05 1600 0.3128 0.8613 0.8658 0.8635 0.9182
0.2869 5.36 1700 0.3121 0.8622 0.8695 0.8658 0.9182
0.2869 5.68 1800 0.3230 0.8473 0.8661 0.8566 0.9140
0.2869 5.99 1900 0.2986 0.8729 0.8633 0.8681 0.9209
0.2134 6.31 2000 0.3032 0.8555 0.8694 0.8624 0.9169
0.2134 6.62 2100 0.3056 0.8705 0.8710 0.8708 0.9220
0.2134 6.94 2200 0.3122 0.8630 0.8790 0.8709 0.9217
0.2134 7.26 2300 0.3047 0.8692 0.8778 0.8734 0.9215
0.2134 7.57 2400 0.3103 0.8701 0.8780 0.8741 0.9225
0.1661 7.89 2500 0.3080 0.8712 0.8787 0.8749 0.9226
0.1661 8.2 2600 0.3011 0.8653 0.8834 0.8743 0.9236
0.1661 8.52 2700 0.3034 0.8735 0.8798 0.8766 0.9247
0.1661 8.83 2800 0.3054 0.8698 0.8793 0.8745 0.9238
0.1661 9.15 2900 0.3105 0.8697 0.8812 0.8754 0.9237
0.1415 9.46 3000 0.3068 0.8738 0.8809 0.8774 0.9246
0.1415 9.78 3100 0.3086 0.8730 0.8793 0.8761 0.9229
0.1415 10.09 3200 0.3013 0.8755 0.8830 0.8792 0.9256
0.1415 10.41 3300 0.3107 0.8692 0.8815 0.8753 0.9241
0.1415 10.73 3400 0.3073 0.8759 0.8794 0.8777 0.9261
0.1239 11.04 3500 0.3109 0.8727 0.8819 0.8773 0.9253
0.1239 11.36 3600 0.3124 0.8723 0.8790 0.8756 0.9243
0.1239 11.67 3700 0.3171 0.8724 0.8805 0.8764 0.9241
0.1239 11.99 3800 0.3081 0.8739 0.8804 0.8771 0.9254
0.1239 12.3 3900 0.3095 0.8735 0.8798 0.8766 0.9254
0.1106 12.62 4000 0.3094 0.8740 0.8796 0.8768 0.9254

Framework versions