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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: test |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/elyadata/Ft%20layoutlmv3%20funsd%20max%20epochs%20100%20%2Cearlystop%3D4%2Cbatch%3D2%2Clr%3D1e-5%20adamw%2CFULL%20models%20params/runs/6zlgssbd) |
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# test |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co./microsoft/layoutlmv3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8476 |
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- Precision: 0.8955 |
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- Recall: 0.9071 |
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- F1: 0.9013 |
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- Accuracy: 0.8691 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 75 | 0.9234 | 0.6139 | 0.7526 | 0.6762 | 0.7416 | |
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| No log | 2.0 | 150 | 0.6101 | 0.7549 | 0.8341 | 0.7925 | 0.7940 | |
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| No log | 3.0 | 225 | 0.5135 | 0.8332 | 0.8882 | 0.8598 | 0.8091 | |
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| No log | 4.0 | 300 | 0.5467 | 0.8189 | 0.8624 | 0.8401 | 0.8109 | |
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| No log | 5.0 | 375 | 0.4879 | 0.8660 | 0.9051 | 0.8851 | 0.8504 | |
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| No log | 6.0 | 450 | 0.5352 | 0.8787 | 0.9180 | 0.8980 | 0.8480 | |
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| 0.5752 | 7.0 | 525 | 0.5900 | 0.8730 | 0.8982 | 0.8854 | 0.8343 | |
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| 0.5752 | 8.0 | 600 | 0.6014 | 0.8832 | 0.9016 | 0.8923 | 0.8506 | |
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| 0.5752 | 9.0 | 675 | 0.6173 | 0.8883 | 0.9126 | 0.9003 | 0.8538 | |
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| 0.5752 | 10.0 | 750 | 0.6278 | 0.8787 | 0.9141 | 0.8960 | 0.8571 | |
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| 0.5752 | 11.0 | 825 | 0.6573 | 0.8612 | 0.9155 | 0.8876 | 0.8326 | |
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| 0.5752 | 12.0 | 900 | 0.7333 | 0.8818 | 0.9006 | 0.8911 | 0.8387 | |
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| 0.5752 | 13.0 | 975 | 0.7489 | 0.8888 | 0.9136 | 0.9010 | 0.8502 | |
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| 0.1263 | 14.0 | 1050 | 0.7719 | 0.8908 | 0.8997 | 0.8952 | 0.8318 | |
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| 0.1263 | 15.0 | 1125 | 0.8295 | 0.8945 | 0.9101 | 0.9022 | 0.8438 | |
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| 0.1263 | 16.0 | 1200 | 0.8447 | 0.8798 | 0.9126 | 0.8959 | 0.8465 | |
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| 0.1263 | 17.0 | 1275 | 0.8359 | 0.9090 | 0.8932 | 0.9010 | 0.8486 | |
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| 0.1263 | 18.0 | 1350 | 0.8430 | 0.8966 | 0.9091 | 0.9028 | 0.8414 | |
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| 0.1263 | 19.0 | 1425 | 0.8179 | 0.8854 | 0.9021 | 0.8937 | 0.8400 | |
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| 0.0482 | 20.0 | 1500 | 0.8950 | 0.8968 | 0.8982 | 0.8975 | 0.8475 | |
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| 0.0482 | 21.0 | 1575 | 0.8790 | 0.9053 | 0.9121 | 0.9087 | 0.8565 | |
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| 0.0482 | 22.0 | 1650 | 0.7915 | 0.9056 | 0.9101 | 0.9078 | 0.8595 | |
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| 0.0482 | 23.0 | 1725 | 0.8760 | 0.8938 | 0.8952 | 0.8945 | 0.8504 | |
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| 0.0482 | 24.0 | 1800 | 0.8320 | 0.9113 | 0.9086 | 0.9100 | 0.8625 | |
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| 0.0482 | 25.0 | 1875 | 0.8880 | 0.9017 | 0.9021 | 0.9019 | 0.8538 | |
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| 0.0482 | 26.0 | 1950 | 0.8611 | 0.9083 | 0.9101 | 0.9092 | 0.8499 | |
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| 0.0163 | 27.0 | 2025 | 0.8747 | 0.9068 | 0.9086 | 0.9077 | 0.8600 | |
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| 0.0163 | 28.0 | 2100 | 0.8476 | 0.8955 | 0.9071 | 0.9013 | 0.8691 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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