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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: layoutlmv2-large-uncased-finetuned-infovqa |
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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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# layoutlmv2-large-uncased-finetuned-infovqa |
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This model is a fine-tuned version of [microsoft/layoutlmv2-large-uncased](https://huggingface.co/microsoft/layoutlmv2-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2207 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 250500 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 4.1829 | 0.08 | 500 | 3.6339 | |
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| 3.5002 | 0.16 | 1000 | 3.0721 | |
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| 2.9556 | 0.24 | 1500 | 2.8731 | |
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| 2.8939 | 0.33 | 2000 | 3.1566 | |
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| 2.6986 | 0.41 | 2500 | 3.1023 | |
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| 2.7569 | 0.49 | 3000 | 2.7743 | |
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| 2.6391 | 0.57 | 3500 | 2.5023 | |
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| 2.4277 | 0.65 | 4000 | 2.5465 | |
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| 2.4242 | 0.73 | 4500 | 2.4709 | |
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| 2.3978 | 0.82 | 5000 | 2.4019 | |
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| 2.2653 | 0.9 | 5500 | 2.3383 | |
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| 2.3916 | 0.98 | 6000 | 2.4765 | |
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| 1.9423 | 1.06 | 6500 | 2.3798 | |
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| 1.8538 | 1.14 | 7000 | 2.3628 | |
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| 1.8136 | 1.22 | 7500 | 2.3671 | |
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| 1.7808 | 1.31 | 8000 | 2.5585 | |
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| 1.7772 | 1.39 | 8500 | 2.5862 | |
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| 1.755 | 1.47 | 9000 | 2.3105 | |
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| 1.6529 | 1.55 | 9500 | 2.2417 | |
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| 1.6956 | 1.63 | 10000 | 2.1755 | |
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| 1.5713 | 1.71 | 10500 | 2.2917 | |
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| 1.565 | 1.79 | 11000 | 2.0838 | |
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| 1.615 | 1.88 | 11500 | 2.2111 | |
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| 1.5249 | 1.96 | 12000 | 2.2207 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.8.0+cu101 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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