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 1.2240 0.6077 0.3766 0.4650 0.7011
No log 0.63 200 0.8417 0.6440 0.5089 0.5685 0.7743
No log 0.95 300 0.6466 0.7243 0.6583 0.6897 0.8311
No log 1.26 400 0.5516 0.7533 0.7158 0.7341 0.8537
0.9961 1.58 500 0.4845 0.7835 0.7557 0.7693 0.8699
0.9961 1.89 600 0.4506 0.7809 0.7930 0.7869 0.8770
0.9961 2.21 700 0.4230 0.8101 0.8107 0.8104 0.8886
0.9961 2.52 800 0.3797 0.8211 0.8296 0.8253 0.8983
0.9961 2.84 900 0.3576 0.8289 0.8411 0.8349 0.9016
0.4076 3.15 1000 0.3430 0.8394 0.8371 0.8382 0.9055
0.4076 3.47 1100 0.3354 0.8531 0.8405 0.8467 0.9071
0.4076 3.79 1200 0.3331 0.8371 0.8504 0.8437 0.9076
0.4076 4.1 1300 0.3184 0.8445 0.8609 0.8526 0.9118
0.4076 4.42 1400 0.3087 0.8617 0.8580 0.8598 0.9150
0.2673 4.73 1500 0.3013 0.8613 0.8657 0.8635 0.9177
0.2673 5.05 1600 0.2971 0.8630 0.8689 0.8659 0.9181
0.2673 5.36 1700 0.3075 0.8675 0.8639 0.8657 0.9177
0.2673 5.68 1800 0.2989 0.8551 0.8764 0.8656 0.9193
0.2673 5.99 1900 0.3011 0.8572 0.8762 0.8666 0.9194
0.2026 6.31 2000 0.3107 0.8595 0.8722 0.8658 0.9181
0.2026 6.62 2100 0.3050 0.8678 0.8800 0.8739 0.9220
0.2026 6.94 2200 0.2971 0.8722 0.8789 0.8755 0.9237
0.2026 7.26 2300 0.3057 0.8666 0.8785 0.8725 0.9209
0.2026 7.57 2400 0.3172 0.8593 0.8773 0.8682 0.9184
0.1647 7.89 2500 0.3018 0.8695 0.8823 0.8759 0.9228
0.1647 8.2 2600 0.3001 0.8760 0.8795 0.8777 0.9256
0.1647 8.52 2700 0.3068 0.8758 0.8745 0.8752 0.9235
0.1647 8.83 2800 0.3007 0.8779 0.8779 0.8779 0.9248
0.1647 9.15 2900 0.3063 0.8740 0.8763 0.8751 0.9228
0.1342 9.46 3000 0.3096 0.8675 0.8834 0.8754 0.9235
0.1342 9.78 3100 0.3052 0.8736 0.8848 0.8792 0.9249
0.1342 10.09 3200 0.3120 0.8727 0.8885 0.8805 0.9252
0.1342 10.41 3300 0.3146 0.8718 0.8843 0.8780 0.9243
0.1342 10.73 3400 0.3124 0.8720 0.8880 0.8799 0.9253
0.117 11.04 3500 0.3088 0.8761 0.8817 0.8789 0.9252
0.117 11.36 3600 0.3082 0.8782 0.8834 0.8808 0.9257
0.117 11.67 3700 0.3129 0.8767 0.8847 0.8807 0.9256
0.117 11.99 3800 0.3116 0.8792 0.8847 0.8820 0.9265
0.117 12.3 3900 0.3142 0.8768 0.8874 0.8821 0.9261
0.1022 12.62 4000 0.3129 0.8780 0.8870 0.8825 0.9265

Framework versions