File size: 15,220 Bytes
72bfe8b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 |
---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLMv3_1
results: []
---
<!-- 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. -->
# LayoutLMv3_1
This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3772
- Precision: 0.7355
- Recall: 0.7550
- F1: 0.7451
- Accuracy: 0.9035
## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.37 | 10 | 2.5352 | 0.0089 | 0.0199 | 0.0123 | 0.0503 |
| No log | 0.74 | 20 | 2.1493 | 0.0377 | 0.0397 | 0.0387 | 0.6028 |
| No log | 1.11 | 30 | 1.7234 | 0.0 | 0.0 | 0.0 | 0.7804 |
| No log | 1.48 | 40 | 1.2971 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 1.85 | 50 | 1.0544 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 2.22 | 60 | 1.0210 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 2.59 | 70 | 0.9842 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 2.96 | 80 | 0.9651 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 3.33 | 90 | 0.9402 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 3.7 | 100 | 0.9205 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 4.07 | 110 | 0.9035 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 4.44 | 120 | 0.8807 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 4.81 | 130 | 0.8596 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 5.19 | 140 | 0.8382 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 5.56 | 150 | 0.8151 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 5.93 | 160 | 0.8039 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 6.3 | 170 | 0.7864 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 6.67 | 180 | 0.7588 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 7.04 | 190 | 0.7352 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 7.41 | 200 | 0.7232 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 7.78 | 210 | 0.7246 | 1.0 | 0.0132 | 0.0261 | 0.7846 |
| No log | 8.15 | 220 | 0.6916 | 1.0 | 0.0132 | 0.0261 | 0.7846 |
| No log | 8.52 | 230 | 0.6755 | 1.0 | 0.0199 | 0.0390 | 0.7860 |
| No log | 8.89 | 240 | 0.6686 | 1.0 | 0.0331 | 0.0641 | 0.7888 |
| No log | 9.26 | 250 | 0.6514 | 1.0 | 0.0265 | 0.0516 | 0.7874 |
| No log | 9.63 | 260 | 0.6430 | 1.0 | 0.0596 | 0.1125 | 0.7944 |
| No log | 10.0 | 270 | 0.6280 | 0.9474 | 0.1192 | 0.2118 | 0.8070 |
| No log | 10.37 | 280 | 0.6127 | 0.9286 | 0.1722 | 0.2905 | 0.8196 |
| No log | 10.74 | 290 | 0.6136 | 0.9024 | 0.2450 | 0.3854 | 0.8350 |
| No log | 11.11 | 300 | 0.5886 | 0.8810 | 0.2450 | 0.3834 | 0.8350 |
| No log | 11.48 | 310 | 0.5896 | 0.8909 | 0.3245 | 0.4757 | 0.8517 |
| No log | 11.85 | 320 | 0.5732 | 0.9310 | 0.3576 | 0.5167 | 0.8587 |
| No log | 12.22 | 330 | 0.5770 | 0.8533 | 0.4238 | 0.5664 | 0.8671 |
| No log | 12.59 | 340 | 0.5557 | 0.8649 | 0.4238 | 0.5689 | 0.8671 |
| No log | 12.96 | 350 | 0.5469 | 0.8222 | 0.4901 | 0.6141 | 0.8797 |
| No log | 13.33 | 360 | 0.5412 | 0.8242 | 0.4967 | 0.6198 | 0.8825 |
| No log | 13.7 | 370 | 0.5313 | 0.8454 | 0.5430 | 0.6613 | 0.8923 |
| No log | 14.07 | 380 | 0.5188 | 0.8381 | 0.5828 | 0.6875 | 0.8993 |
| No log | 14.44 | 390 | 0.5190 | 0.8333 | 0.5960 | 0.6950 | 0.8993 |
| No log | 14.81 | 400 | 0.5172 | 0.8165 | 0.5894 | 0.6846 | 0.8993 |
| No log | 15.19 | 410 | 0.5066 | 0.7966 | 0.6225 | 0.6989 | 0.9021 |
| No log | 15.56 | 420 | 0.4879 | 0.8087 | 0.6159 | 0.6992 | 0.9035 |
| No log | 15.93 | 430 | 0.4943 | 0.7833 | 0.6225 | 0.6937 | 0.9021 |
| No log | 16.3 | 440 | 0.4716 | 0.8205 | 0.6358 | 0.7164 | 0.9091 |
| No log | 16.67 | 450 | 0.4594 | 0.8264 | 0.6623 | 0.7353 | 0.9119 |
| No log | 17.04 | 460 | 0.4758 | 0.7761 | 0.6887 | 0.7298 | 0.9105 |
| No log | 17.41 | 470 | 0.4520 | 0.8430 | 0.6755 | 0.75 | 0.9217 |
| No log | 17.78 | 480 | 0.4582 | 0.8244 | 0.7152 | 0.7660 | 0.9245 |
| No log | 18.15 | 490 | 0.4475 | 0.8189 | 0.6887 | 0.7482 | 0.9217 |
| 0.6982 | 18.52 | 500 | 0.4627 | 0.7431 | 0.7086 | 0.7254 | 0.9105 |
| 0.6982 | 18.89 | 510 | 0.4419 | 0.7826 | 0.7152 | 0.7474 | 0.9189 |
| 0.6982 | 19.26 | 520 | 0.4351 | 0.7730 | 0.7219 | 0.7466 | 0.9147 |
| 0.6982 | 19.63 | 530 | 0.4213 | 0.7857 | 0.7285 | 0.7560 | 0.9189 |
| 0.6982 | 20.0 | 540 | 0.4389 | 0.7273 | 0.7417 | 0.7344 | 0.9091 |
| 0.6982 | 20.37 | 550 | 0.4208 | 0.7762 | 0.7351 | 0.7551 | 0.9189 |
| 0.6982 | 20.74 | 560 | 0.4301 | 0.74 | 0.7351 | 0.7375 | 0.9119 |
| 0.6982 | 21.11 | 570 | 0.4199 | 0.7568 | 0.7417 | 0.7492 | 0.9161 |
| 0.6982 | 21.48 | 580 | 0.4283 | 0.7006 | 0.7285 | 0.7143 | 0.9021 |
| 0.6982 | 21.85 | 590 | 0.4068 | 0.7857 | 0.7285 | 0.7560 | 0.9203 |
| 0.6982 | 22.22 | 600 | 0.4241 | 0.7179 | 0.7417 | 0.7296 | 0.9077 |
| 0.6982 | 22.59 | 610 | 0.3988 | 0.8321 | 0.7550 | 0.7917 | 0.9329 |
| 0.6982 | 22.96 | 620 | 0.4005 | 0.7671 | 0.7417 | 0.7542 | 0.9189 |
| 0.6982 | 23.33 | 630 | 0.3939 | 0.7651 | 0.7550 | 0.76 | 0.9189 |
| 0.6982 | 23.7 | 640 | 0.4007 | 0.7278 | 0.7616 | 0.7443 | 0.9119 |
| 0.6982 | 24.07 | 650 | 0.3857 | 0.7973 | 0.7815 | 0.7893 | 0.9217 |
| 0.6982 | 24.44 | 660 | 0.3893 | 0.7682 | 0.7682 | 0.7682 | 0.9175 |
| 0.6982 | 24.81 | 670 | 0.3946 | 0.7516 | 0.7616 | 0.7566 | 0.9147 |
| 0.6982 | 25.19 | 680 | 0.3893 | 0.7516 | 0.7616 | 0.7566 | 0.9161 |
| 0.6982 | 25.56 | 690 | 0.3969 | 0.7419 | 0.7616 | 0.7516 | 0.9119 |
| 0.6982 | 25.93 | 700 | 0.3854 | 0.7852 | 0.7748 | 0.7800 | 0.9217 |
| 0.6982 | 26.3 | 710 | 0.3858 | 0.7973 | 0.7815 | 0.7893 | 0.9231 |
| 0.6982 | 26.67 | 720 | 0.3831 | 0.7867 | 0.7815 | 0.7841 | 0.9217 |
| 0.6982 | 27.04 | 730 | 0.3996 | 0.7267 | 0.7748 | 0.75 | 0.9049 |
| 0.6982 | 27.41 | 740 | 0.3907 | 0.7358 | 0.7748 | 0.7548 | 0.9077 |
| 0.6982 | 27.78 | 750 | 0.3720 | 0.8013 | 0.8013 | 0.8013 | 0.9245 |
| 0.6982 | 28.15 | 760 | 0.3799 | 0.7895 | 0.7947 | 0.7921 | 0.9189 |
| 0.6982 | 28.52 | 770 | 0.3938 | 0.7178 | 0.7748 | 0.7452 | 0.9035 |
| 0.6982 | 28.89 | 780 | 0.3761 | 0.7763 | 0.7815 | 0.7789 | 0.9189 |
| 0.6982 | 29.26 | 790 | 0.3906 | 0.7267 | 0.7748 | 0.75 | 0.9063 |
| 0.6982 | 29.63 | 800 | 0.3780 | 0.7436 | 0.7682 | 0.7557 | 0.9105 |
| 0.6982 | 30.0 | 810 | 0.3773 | 0.7548 | 0.7748 | 0.7647 | 0.9133 |
| 0.6982 | 30.37 | 820 | 0.3716 | 0.7727 | 0.7881 | 0.7803 | 0.9175 |
| 0.6982 | 30.74 | 830 | 0.3747 | 0.7452 | 0.7748 | 0.7597 | 0.9119 |
| 0.6982 | 31.11 | 840 | 0.3747 | 0.7405 | 0.7748 | 0.7573 | 0.9133 |
| 0.6982 | 31.48 | 850 | 0.3821 | 0.7239 | 0.7815 | 0.7516 | 0.9077 |
| 0.6982 | 31.85 | 860 | 0.3649 | 0.7697 | 0.7748 | 0.7723 | 0.9175 |
| 0.6982 | 32.22 | 870 | 0.3804 | 0.7152 | 0.7815 | 0.7468 | 0.9049 |
| 0.6982 | 32.59 | 880 | 0.3715 | 0.75 | 0.7748 | 0.7622 | 0.9105 |
| 0.6982 | 32.96 | 890 | 0.3663 | 0.7632 | 0.7682 | 0.7657 | 0.9161 |
| 0.6982 | 33.33 | 900 | 0.3713 | 0.7516 | 0.7815 | 0.7662 | 0.9133 |
| 0.6982 | 33.7 | 910 | 0.3684 | 0.7597 | 0.7748 | 0.7672 | 0.9133 |
| 0.6982 | 34.07 | 920 | 0.3708 | 0.75 | 0.7748 | 0.7622 | 0.9119 |
| 0.6982 | 34.44 | 930 | 0.3699 | 0.8146 | 0.8146 | 0.8146 | 0.9259 |
| 0.6982 | 34.81 | 940 | 0.3726 | 0.7778 | 0.7881 | 0.7829 | 0.9189 |
| 0.6982 | 35.19 | 950 | 0.3763 | 0.7405 | 0.7748 | 0.7573 | 0.9105 |
| 0.6982 | 35.56 | 960 | 0.3883 | 0.7267 | 0.7748 | 0.75 | 0.9035 |
| 0.6982 | 35.93 | 970 | 0.3729 | 0.7616 | 0.7616 | 0.7616 | 0.9119 |
| 0.6982 | 36.3 | 980 | 0.3654 | 0.8108 | 0.7947 | 0.8027 | 0.9217 |
| 0.6982 | 36.67 | 990 | 0.3795 | 0.7195 | 0.7815 | 0.7492 | 0.9049 |
| 0.2195 | 37.04 | 1000 | 0.3819 | 0.7267 | 0.7748 | 0.75 | 0.9035 |
| 0.2195 | 37.41 | 1010 | 0.3760 | 0.7233 | 0.7616 | 0.7419 | 0.9035 |
| 0.2195 | 37.78 | 1020 | 0.3664 | 0.7468 | 0.7616 | 0.7541 | 0.9105 |
| 0.2195 | 38.15 | 1030 | 0.3753 | 0.7312 | 0.7748 | 0.7524 | 0.9077 |
| 0.2195 | 38.52 | 1040 | 0.3791 | 0.7284 | 0.7815 | 0.7540 | 0.9035 |
| 0.2195 | 38.89 | 1050 | 0.3665 | 0.7933 | 0.7881 | 0.7907 | 0.9203 |
| 0.2195 | 39.26 | 1060 | 0.3655 | 0.7763 | 0.7815 | 0.7789 | 0.9161 |
| 0.2195 | 39.63 | 1070 | 0.3811 | 0.7312 | 0.7748 | 0.7524 | 0.9091 |
| 0.2195 | 40.0 | 1080 | 0.3725 | 0.7342 | 0.7682 | 0.7508 | 0.9063 |
| 0.2195 | 40.37 | 1090 | 0.3639 | 0.7692 | 0.7947 | 0.7818 | 0.9161 |
| 0.2195 | 40.74 | 1100 | 0.3721 | 0.7312 | 0.7748 | 0.7524 | 0.9077 |
| 0.2195 | 41.11 | 1110 | 0.3782 | 0.7143 | 0.7616 | 0.7372 | 0.9021 |
| 0.2195 | 41.48 | 1120 | 0.3654 | 0.7748 | 0.7748 | 0.7748 | 0.9189 |
| 0.2195 | 41.85 | 1130 | 0.3717 | 0.7278 | 0.7616 | 0.7443 | 0.9049 |
| 0.2195 | 42.22 | 1140 | 0.3868 | 0.7195 | 0.7815 | 0.7492 | 0.9021 |
| 0.2195 | 42.59 | 1150 | 0.3913 | 0.7066 | 0.7815 | 0.7421 | 0.8993 |
| 0.2195 | 42.96 | 1160 | 0.3797 | 0.7222 | 0.7748 | 0.7476 | 0.9035 |
| 0.2195 | 43.33 | 1170 | 0.3709 | 0.7405 | 0.7748 | 0.7573 | 0.9105 |
| 0.2195 | 43.7 | 1180 | 0.3736 | 0.7358 | 0.7748 | 0.7548 | 0.9077 |
| 0.2195 | 44.07 | 1190 | 0.3664 | 0.7389 | 0.7682 | 0.7532 | 0.9091 |
| 0.2195 | 44.44 | 1200 | 0.3677 | 0.7358 | 0.7748 | 0.7548 | 0.9063 |
| 0.2195 | 44.81 | 1210 | 0.3805 | 0.7329 | 0.7815 | 0.7564 | 0.9077 |
| 0.2195 | 45.19 | 1220 | 0.3806 | 0.7329 | 0.7815 | 0.7564 | 0.9077 |
| 0.2195 | 45.56 | 1230 | 0.3712 | 0.7372 | 0.7616 | 0.7492 | 0.9035 |
| 0.2195 | 45.93 | 1240 | 0.3746 | 0.7308 | 0.7550 | 0.7427 | 0.9035 |
| 0.2195 | 46.3 | 1250 | 0.3725 | 0.7261 | 0.7550 | 0.7403 | 0.9049 |
| 0.2195 | 46.67 | 1260 | 0.3719 | 0.7355 | 0.7550 | 0.7451 | 0.9035 |
| 0.2195 | 47.04 | 1270 | 0.3718 | 0.7355 | 0.7550 | 0.7451 | 0.9063 |
| 0.2195 | 47.41 | 1280 | 0.3728 | 0.7355 | 0.7550 | 0.7451 | 0.9063 |
| 0.2195 | 47.78 | 1290 | 0.3740 | 0.7261 | 0.7550 | 0.7403 | 0.9035 |
| 0.2195 | 48.15 | 1300 | 0.3780 | 0.7325 | 0.7616 | 0.7468 | 0.9035 |
| 0.2195 | 48.52 | 1310 | 0.3796 | 0.7325 | 0.7616 | 0.7468 | 0.9035 |
| 0.2195 | 48.89 | 1320 | 0.3816 | 0.7325 | 0.7616 | 0.7468 | 0.9035 |
| 0.2195 | 49.26 | 1330 | 0.3816 | 0.7278 | 0.7616 | 0.7443 | 0.9021 |
| 0.2195 | 49.63 | 1340 | 0.3803 | 0.7278 | 0.7616 | 0.7443 | 0.9021 |
| 0.2195 | 50.0 | 1350 | 0.3777 | 0.7308 | 0.7550 | 0.7427 | 0.9049 |
| 0.2195 | 50.37 | 1360 | 0.3810 | 0.7325 | 0.7616 | 0.7468 | 0.9035 |
| 0.2195 | 50.74 | 1370 | 0.3793 | 0.7325 | 0.7616 | 0.7468 | 0.9063 |
| 0.2195 | 51.11 | 1380 | 0.3773 | 0.7308 | 0.7550 | 0.7427 | 0.9049 |
| 0.2195 | 51.48 | 1390 | 0.3791 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 51.85 | 1400 | 0.3822 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 52.22 | 1410 | 0.3830 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 52.59 | 1420 | 0.3797 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 52.96 | 1430 | 0.3791 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 53.33 | 1440 | 0.3790 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 53.7 | 1450 | 0.3792 | 0.7342 | 0.7682 | 0.7508 | 0.9049 |
| 0.2195 | 54.07 | 1460 | 0.3786 | 0.7325 | 0.7616 | 0.7468 | 0.9035 |
| 0.2195 | 54.44 | 1470 | 0.3778 | 0.7355 | 0.7550 | 0.7451 | 0.9035 |
| 0.2195 | 54.81 | 1480 | 0.3776 | 0.7355 | 0.7550 | 0.7451 | 0.9035 |
| 0.2195 | 55.19 | 1490 | 0.3774 | 0.7355 | 0.7550 | 0.7451 | 0.9035 |
| 0.1305 | 55.56 | 1500 | 0.3772 | 0.7355 | 0.7550 | 0.7451 | 0.9035 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|