File size: 20,189 Bytes
f4d5a3c |
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 |
---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 2024-01-03_one_stage_subgraphs_weighted_txt_vis_conc_1_4_8_12_ramp
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. -->
# 2024-01-03_one_stage_subgraphs_weighted_txt_vis_conc_1_4_8_12_ramp
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8574
- Accuracy: 0.77
- Exit 0 Accuracy: 0.2
- Exit 1 Accuracy: 0.3
- Exit 2 Accuracy: 0.1125
- Exit 3 Accuracy: 0.2725
- Exit 4 Accuracy: 0.2675
- Exit 5 Accuracy: 0.51
- Exit 6 Accuracy: 0.55
- Exit 7 Accuracy: 0.63
- Exit 8 Accuracy: 0.525
- Exit 9 Accuracy: 0.3425
- Exit 10 Accuracy: 0.445
- Exit 11 Accuracy: 0.6875
- Exit 12 Accuracy: 0.7575
## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 24
- total_train_batch_size: 192
- 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 | Exit 2 Accuracy | Exit 3 Accuracy | Exit 4 Accuracy | Exit 5 Accuracy | Exit 6 Accuracy | Exit 7 Accuracy | Exit 8 Accuracy | Exit 9 Accuracy | Exit 10 Accuracy | Exit 11 Accuracy | Exit 12 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|:----------------:|:----------------:|:----------------:|
| No log | 0.96 | 4 | 2.7477 | 0.1025 | 0.07 | 0.0625 | 0.0625 | 0.0625 | 0.06 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.06 |
| No log | 1.96 | 8 | 2.7020 | 0.1275 | 0.0775 | 0.0625 | 0.0625 | 0.0625 | 0.0575 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.06 |
| No log | 2.96 | 12 | 2.6514 | 0.19 | 0.08 | 0.0625 | 0.0625 | 0.0625 | 0.065 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.065 |
| No log | 3.96 | 16 | 2.5720 | 0.215 | 0.095 | 0.065 | 0.0625 | 0.0625 | 0.06 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0925 |
| No log | 4.96 | 20 | 2.5033 | 0.2375 | 0.1 | 0.0675 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.1475 |
| No log | 5.96 | 24 | 2.4003 | 0.275 | 0.115 | 0.08 | 0.0625 | 0.0625 | 0.0625 | 0.0775 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.1525 |
| No log | 6.96 | 28 | 2.3192 | 0.3 | 0.12 | 0.0875 | 0.0625 | 0.0625 | 0.0625 | 0.09 | 0.075 | 0.065 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.1625 |
| No log | 7.96 | 32 | 2.2199 | 0.3325 | 0.1325 | 0.0875 | 0.0625 | 0.0625 | 0.0625 | 0.1025 | 0.075 | 0.065 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.185 |
| No log | 8.96 | 36 | 2.1335 | 0.36 | 0.1425 | 0.1025 | 0.0625 | 0.0625 | 0.0625 | 0.1375 | 0.09 | 0.07 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.235 |
| No log | 9.96 | 40 | 2.0290 | 0.4 | 0.1475 | 0.1025 | 0.0625 | 0.0625 | 0.06 | 0.15 | 0.0925 | 0.0725 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.27 |
| No log | 10.96 | 44 | 1.9285 | 0.4525 | 0.155 | 0.1025 | 0.0625 | 0.065 | 0.0675 | 0.1725 | 0.1225 | 0.08 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.305 |
| No log | 11.96 | 48 | 1.8071 | 0.495 | 0.155 | 0.1075 | 0.0625 | 0.0775 | 0.0825 | 0.2025 | 0.135 | 0.0925 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.355 |
| No log | 12.96 | 52 | 1.7194 | 0.5375 | 0.16 | 0.1075 | 0.0625 | 0.0775 | 0.0875 | 0.22 | 0.1625 | 0.1025 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.37 |
| No log | 13.96 | 56 | 1.5732 | 0.6 | 0.1625 | 0.11 | 0.0625 | 0.08 | 0.0775 | 0.2425 | 0.2125 | 0.14 | 0.0625 | 0.0625 | 0.0625 | 0.0625 | 0.43 |
| No log | 14.96 | 60 | 1.5141 | 0.6125 | 0.16 | 0.115 | 0.0625 | 0.0825 | 0.09 | 0.29 | 0.245 | 0.18 | 0.0625 | 0.065 | 0.0625 | 0.0625 | 0.4325 |
| No log | 15.96 | 64 | 1.4049 | 0.65 | 0.1575 | 0.1175 | 0.0625 | 0.0925 | 0.1 | 0.3275 | 0.2725 | 0.24 | 0.0675 | 0.065 | 0.0625 | 0.0625 | 0.51 |
| No log | 16.96 | 68 | 1.3476 | 0.665 | 0.16 | 0.115 | 0.0625 | 0.095 | 0.1025 | 0.345 | 0.285 | 0.2625 | 0.0675 | 0.075 | 0.0625 | 0.0625 | 0.5275 |
| No log | 17.96 | 72 | 1.2825 | 0.6925 | 0.16 | 0.1175 | 0.0625 | 0.1025 | 0.11 | 0.35 | 0.2875 | 0.2925 | 0.0675 | 0.075 | 0.065 | 0.0625 | 0.55 |
| No log | 18.96 | 76 | 1.2102 | 0.71 | 0.16 | 0.1175 | 0.0625 | 0.1025 | 0.135 | 0.365 | 0.29 | 0.31 | 0.0675 | 0.0775 | 0.08 | 0.0625 | 0.5925 |
| No log | 19.96 | 80 | 1.1664 | 0.725 | 0.16 | 0.1175 | 0.0625 | 0.1125 | 0.1325 | 0.3675 | 0.3075 | 0.365 | 0.0775 | 0.0775 | 0.08 | 0.0625 | 0.6025 |
| No log | 20.96 | 84 | 1.1363 | 0.735 | 0.16 | 0.12 | 0.0625 | 0.115 | 0.145 | 0.3725 | 0.3275 | 0.3775 | 0.0775 | 0.075 | 0.07 | 0.0625 | 0.6175 |
| No log | 21.96 | 88 | 1.0745 | 0.74 | 0.16 | 0.1225 | 0.0625 | 0.1175 | 0.1325 | 0.375 | 0.355 | 0.4175 | 0.0775 | 0.0825 | 0.065 | 0.0625 | 0.6275 |
| No log | 22.96 | 92 | 1.0377 | 0.7525 | 0.16 | 0.13 | 0.0625 | 0.115 | 0.1575 | 0.38 | 0.3775 | 0.4125 | 0.0825 | 0.075 | 0.07 | 0.0625 | 0.64 |
| No log | 23.96 | 96 | 1.0321 | 0.74 | 0.16 | 0.1375 | 0.0625 | 0.115 | 0.165 | 0.3825 | 0.385 | 0.4375 | 0.08 | 0.0975 | 0.07 | 0.0625 | 0.66 |
| No log | 24.96 | 100 | 0.9702 | 0.76 | 0.1625 | 0.15 | 0.0625 | 0.11 | 0.1725 | 0.385 | 0.4075 | 0.455 | 0.0825 | 0.0975 | 0.0725 | 0.0625 | 0.68 |
| No log | 25.96 | 104 | 0.9861 | 0.7525 | 0.1675 | 0.1525 | 0.0625 | 0.1125 | 0.1825 | 0.395 | 0.4 | 0.4675 | 0.0825 | 0.115 | 0.0675 | 0.07 | 0.6825 |
| No log | 26.96 | 108 | 0.9339 | 0.7525 | 0.16 | 0.15 | 0.0625 | 0.1175 | 0.195 | 0.4075 | 0.4275 | 0.4825 | 0.0875 | 0.13 | 0.07 | 0.095 | 0.7025 |
| No log | 27.96 | 112 | 0.9362 | 0.7575 | 0.1625 | 0.1425 | 0.0625 | 0.1175 | 0.1925 | 0.4175 | 0.43 | 0.515 | 0.095 | 0.14 | 0.0675 | 0.105 | 0.71 |
| No log | 28.96 | 116 | 0.8872 | 0.755 | 0.165 | 0.15 | 0.0625 | 0.1175 | 0.2 | 0.4275 | 0.4325 | 0.53 | 0.095 | 0.1425 | 0.07 | 0.125 | 0.7425 |
| No log | 29.96 | 120 | 0.8939 | 0.7675 | 0.1625 | 0.15 | 0.0625 | 0.1175 | 0.2 | 0.4475 | 0.4325 | 0.55 | 0.1 | 0.1425 | 0.085 | 0.1325 | 0.7175 |
| No log | 30.96 | 124 | 0.8767 | 0.7475 | 0.16 | 0.1575 | 0.0625 | 0.12 | 0.195 | 0.4425 | 0.4475 | 0.545 | 0.1 | 0.1525 | 0.0925 | 0.2025 | 0.7575 |
| No log | 31.96 | 128 | 0.8658 | 0.76 | 0.165 | 0.17 | 0.0625 | 0.1225 | 0.195 | 0.455 | 0.455 | 0.555 | 0.1025 | 0.1375 | 0.11 | 0.245 | 0.7375 |
| No log | 32.96 | 132 | 0.8736 | 0.7625 | 0.165 | 0.1875 | 0.0625 | 0.125 | 0.195 | 0.465 | 0.45 | 0.5625 | 0.105 | 0.155 | 0.0975 | 0.275 | 0.7575 |
| No log | 33.96 | 136 | 0.8380 | 0.7625 | 0.1675 | 0.21 | 0.0625 | 0.125 | 0.195 | 0.465 | 0.4625 | 0.565 | 0.1175 | 0.13 | 0.115 | 0.3225 | 0.755 |
| No log | 34.96 | 140 | 0.8386 | 0.7725 | 0.1675 | 0.2325 | 0.0625 | 0.1275 | 0.1975 | 0.4675 | 0.4575 | 0.575 | 0.12 | 0.125 | 0.13 | 0.345 | 0.765 |
| No log | 35.96 | 144 | 0.8610 | 0.755 | 0.17 | 0.2425 | 0.0625 | 0.1275 | 0.19 | 0.4625 | 0.4725 | 0.5875 | 0.13 | 0.105 | 0.18 | 0.39 | 0.755 |
| No log | 36.96 | 148 | 0.8444 | 0.76 | 0.17 | 0.255 | 0.0625 | 0.1325 | 0.2 | 0.4575 | 0.4675 | 0.595 | 0.12 | 0.1475 | 0.22 | 0.445 | 0.7525 |
| No log | 37.96 | 152 | 0.8845 | 0.75 | 0.1725 | 0.2725 | 0.0625 | 0.1375 | 0.205 | 0.46 | 0.475 | 0.59 | 0.1425 | 0.175 | 0.255 | 0.45 | 0.7575 |
| No log | 38.96 | 156 | 0.8464 | 0.7625 | 0.18 | 0.275 | 0.0625 | 0.145 | 0.2075 | 0.4675 | 0.4825 | 0.5925 | 0.18 | 0.22 | 0.265 | 0.51 | 0.755 |
| No log | 39.96 | 160 | 0.8539 | 0.7575 | 0.1825 | 0.2825 | 0.065 | 0.1475 | 0.215 | 0.48 | 0.515 | 0.6025 | 0.2 | 0.2425 | 0.2725 | 0.5275 | 0.755 |
| No log | 40.96 | 164 | 0.8697 | 0.76 | 0.185 | 0.2775 | 0.0675 | 0.1525 | 0.23 | 0.485 | 0.5325 | 0.605 | 0.2175 | 0.21 | 0.29 | 0.53 | 0.7625 |
| No log | 41.96 | 168 | 0.8395 | 0.775 | 0.185 | 0.2825 | 0.075 | 0.16 | 0.2225 | 0.4925 | 0.54 | 0.6 | 0.225 | 0.225 | 0.2875 | 0.5725 | 0.77 |
| No log | 42.96 | 172 | 0.8570 | 0.7675 | 0.1875 | 0.285 | 0.08 | 0.1575 | 0.2275 | 0.485 | 0.5475 | 0.61 | 0.2325 | 0.2325 | 0.3075 | 0.6075 | 0.7525 |
| No log | 43.96 | 176 | 0.8462 | 0.765 | 0.195 | 0.28 | 0.08 | 0.165 | 0.2325 | 0.49 | 0.5425 | 0.6125 | 0.2475 | 0.2425 | 0.3125 | 0.6225 | 0.755 |
| No log | 44.96 | 180 | 0.8563 | 0.765 | 0.195 | 0.2825 | 0.085 | 0.1775 | 0.235 | 0.495 | 0.535 | 0.6075 | 0.2975 | 0.22 | 0.3175 | 0.62 | 0.75 |
| No log | 45.96 | 184 | 0.8670 | 0.7675 | 0.195 | 0.28 | 0.085 | 0.1825 | 0.24 | 0.4975 | 0.54 | 0.615 | 0.3525 | 0.215 | 0.325 | 0.6375 | 0.76 |
| No log | 46.96 | 188 | 0.8708 | 0.77 | 0.195 | 0.29 | 0.0925 | 0.185 | 0.2375 | 0.4975 | 0.535 | 0.6125 | 0.365 | 0.2275 | 0.3175 | 0.64 | 0.7575 |
| No log | 47.96 | 192 | 0.8535 | 0.7675 | 0.19 | 0.29 | 0.095 | 0.2075 | 0.24 | 0.4975 | 0.5375 | 0.6125 | 0.4025 | 0.24 | 0.35 | 0.6575 | 0.755 |
| No log | 48.96 | 196 | 0.8592 | 0.765 | 0.19 | 0.285 | 0.0975 | 0.2175 | 0.2425 | 0.495 | 0.54 | 0.615 | 0.4175 | 0.2375 | 0.365 | 0.6575 | 0.7475 |
| No log | 49.96 | 200 | 0.8717 | 0.765 | 0.19 | 0.2925 | 0.1 | 0.235 | 0.25 | 0.5 | 0.545 | 0.6125 | 0.4325 | 0.25 | 0.3725 | 0.66 | 0.76 |
| No log | 50.96 | 204 | 0.8684 | 0.765 | 0.1925 | 0.2975 | 0.105 | 0.245 | 0.2575 | 0.5025 | 0.545 | 0.61 | 0.4475 | 0.2775 | 0.3775 | 0.675 | 0.7625 |
| No log | 51.96 | 208 | 0.8662 | 0.76 | 0.1925 | 0.295 | 0.1025 | 0.245 | 0.2625 | 0.5025 | 0.55 | 0.6175 | 0.455 | 0.2925 | 0.39 | 0.68 | 0.76 |
| No log | 52.96 | 212 | 0.8718 | 0.7625 | 0.1925 | 0.295 | 0.1075 | 0.2525 | 0.2625 | 0.5025 | 0.55 | 0.6225 | 0.485 | 0.3075 | 0.4125 | 0.6825 | 0.755 |
| No log | 53.96 | 216 | 0.8798 | 0.76 | 0.195 | 0.295 | 0.11 | 0.265 | 0.2625 | 0.505 | 0.5475 | 0.6275 | 0.495 | 0.3175 | 0.4275 | 0.68 | 0.7475 |
| No log | 54.96 | 220 | 0.8703 | 0.7575 | 0.2 | 0.2975 | 0.11 | 0.2675 | 0.2675 | 0.5075 | 0.545 | 0.6225 | 0.4975 | 0.3275 | 0.435 | 0.6825 | 0.745 |
| No log | 55.96 | 224 | 0.8622 | 0.765 | 0.2 | 0.3 | 0.11 | 0.265 | 0.27 | 0.51 | 0.545 | 0.625 | 0.505 | 0.33 | 0.435 | 0.69 | 0.7525 |
| No log | 56.96 | 228 | 0.8590 | 0.77 | 0.2 | 0.3 | 0.11 | 0.27 | 0.2675 | 0.5125 | 0.5475 | 0.6325 | 0.5075 | 0.34 | 0.4375 | 0.6875 | 0.76 |
| No log | 57.96 | 232 | 0.8572 | 0.7725 | 0.2 | 0.3025 | 0.11 | 0.27 | 0.2675 | 0.51 | 0.5475 | 0.6325 | 0.5175 | 0.34 | 0.44 | 0.6875 | 0.7575 |
| No log | 58.96 | 236 | 0.8570 | 0.7725 | 0.2 | 0.3025 | 0.1125 | 0.2725 | 0.2675 | 0.51 | 0.55 | 0.6325 | 0.5225 | 0.34 | 0.445 | 0.6875 | 0.76 |
| No log | 59.96 | 240 | 0.8574 | 0.77 | 0.2 | 0.3 | 0.1125 | 0.2725 | 0.2675 | 0.51 | 0.55 | 0.63 | 0.525 | 0.3425 | 0.445 | 0.6875 | 0.7575 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
|