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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 2024-01-02_one_stage_subgraphs_entropyreg_txt_vis_conc_6_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. -->
# 2024-01-02_one_stage_subgraphs_entropyreg_txt_vis_conc_6_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: 1.1266
- Accuracy: 0.705
- Exit 0 Accuracy: 0.195
- Exit 1 Accuracy: 0.7025
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|
| No log | 0.96 | 4 | 2.7544 | 0.115 | 0.0575 | 0.0625 |
| No log | 1.96 | 8 | 2.6911 | 0.135 | 0.125 | 0.0625 |
| No log | 2.96 | 12 | 2.6410 | 0.1775 | 0.1225 | 0.18 |
| No log | 3.96 | 16 | 2.5664 | 0.2025 | 0.125 | 0.1825 |
| No log | 4.96 | 20 | 2.5036 | 0.2475 | 0.1225 | 0.2475 |
| No log | 5.96 | 24 | 2.4172 | 0.28 | 0.12 | 0.2275 |
| No log | 6.96 | 28 | 2.3247 | 0.3 | 0.1275 | 0.2225 |
| No log | 7.96 | 32 | 2.2355 | 0.36 | 0.14 | 0.2525 |
| No log | 8.96 | 36 | 2.1384 | 0.4025 | 0.1375 | 0.315 |
| No log | 9.96 | 40 | 2.0150 | 0.465 | 0.14 | 0.3475 |
| No log | 10.96 | 44 | 1.9193 | 0.4925 | 0.1425 | 0.37 |
| No log | 11.96 | 48 | 1.7777 | 0.5375 | 0.145 | 0.4325 |
| No log | 12.96 | 52 | 1.6960 | 0.56 | 0.15 | 0.5 |
| No log | 13.96 | 56 | 1.5905 | 0.59 | 0.155 | 0.49 |
| No log | 14.96 | 60 | 1.5197 | 0.625 | 0.155 | 0.5275 |
| No log | 15.96 | 64 | 1.4335 | 0.6475 | 0.1525 | 0.5425 |
| No log | 16.96 | 68 | 1.3831 | 0.6575 | 0.1575 | 0.5675 |
| No log | 17.96 | 72 | 1.3216 | 0.6775 | 0.155 | 0.575 |
| No log | 18.96 | 76 | 1.2973 | 0.6825 | 0.1575 | 0.5825 |
| No log | 19.96 | 80 | 1.2342 | 0.6975 | 0.1575 | 0.6025 |
| No log | 20.96 | 84 | 1.2190 | 0.6825 | 0.16 | 0.605 |
| No log | 21.96 | 88 | 1.1758 | 0.7125 | 0.1625 | 0.62 |
| No log | 22.96 | 92 | 1.1612 | 0.685 | 0.1675 | 0.625 |
| No log | 23.96 | 96 | 1.1329 | 0.6925 | 0.1675 | 0.64 |
| No log | 24.96 | 100 | 1.1001 | 0.7125 | 0.1675 | 0.635 |
| No log | 25.96 | 104 | 1.0943 | 0.7025 | 0.175 | 0.645 |
| No log | 26.96 | 108 | 1.0794 | 0.7125 | 0.18 | 0.6475 |
| No log | 27.96 | 112 | 1.0919 | 0.6925 | 0.185 | 0.6475 |
| No log | 28.96 | 116 | 1.0630 | 0.72 | 0.1875 | 0.6575 |
| No log | 29.96 | 120 | 1.0831 | 0.7 | 0.1875 | 0.655 |
| No log | 30.96 | 124 | 1.0581 | 0.695 | 0.1875 | 0.6625 |
| No log | 31.96 | 128 | 1.0588 | 0.715 | 0.1875 | 0.66 |
| No log | 32.96 | 132 | 1.0624 | 0.6975 | 0.185 | 0.675 |
| No log | 33.96 | 136 | 1.0355 | 0.71 | 0.1875 | 0.675 |
| No log | 34.96 | 140 | 1.0777 | 0.6925 | 0.1875 | 0.665 |
| No log | 35.96 | 144 | 1.0514 | 0.71 | 0.19 | 0.675 |
| No log | 36.96 | 148 | 1.0678 | 0.7 | 0.1925 | 0.6825 |
| No log | 37.96 | 152 | 1.0610 | 0.7025 | 0.1925 | 0.68 |
| No log | 38.96 | 156 | 1.0726 | 0.7025 | 0.195 | 0.69 |
| No log | 39.96 | 160 | 1.0818 | 0.7025 | 0.195 | 0.69 |
| No log | 40.96 | 164 | 1.0893 | 0.6975 | 0.1925 | 0.685 |
| No log | 41.96 | 168 | 1.0980 | 0.695 | 0.195 | 0.69 |
| No log | 42.96 | 172 | 1.1009 | 0.7025 | 0.1925 | 0.6925 |
| No log | 43.96 | 176 | 1.0896 | 0.705 | 0.1925 | 0.695 |
| No log | 44.96 | 180 | 1.0697 | 0.7125 | 0.1925 | 0.695 |
| No log | 45.96 | 184 | 1.1185 | 0.7025 | 0.1925 | 0.695 |
| No log | 46.96 | 188 | 1.0956 | 0.705 | 0.1925 | 0.6925 |
| No log | 47.96 | 192 | 1.1095 | 0.71 | 0.19 | 0.6975 |
| No log | 48.96 | 196 | 1.1233 | 0.7075 | 0.1925 | 0.7025 |
| No log | 49.96 | 200 | 1.1281 | 0.705 | 0.1925 | 0.7025 |
| No log | 50.96 | 204 | 1.1428 | 0.6975 | 0.1925 | 0.7025 |
| No log | 51.96 | 208 | 1.1292 | 0.7025 | 0.1925 | 0.71 |
| No log | 52.96 | 212 | 1.1218 | 0.7025 | 0.19 | 0.7125 |
| No log | 53.96 | 216 | 1.1143 | 0.7075 | 0.1925 | 0.7025 |
| No log | 54.96 | 220 | 1.1192 | 0.7125 | 0.195 | 0.7025 |
| No log | 55.96 | 224 | 1.1338 | 0.715 | 0.195 | 0.7025 |
| No log | 56.96 | 228 | 1.1333 | 0.71 | 0.195 | 0.7075 |
| No log | 57.96 | 232 | 1.1291 | 0.7025 | 0.195 | 0.7025 |
| No log | 58.96 | 236 | 1.1268 | 0.705 | 0.195 | 0.705 |
| No log | 59.96 | 240 | 1.1266 | 0.705 | 0.195 | 0.7025 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
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