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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv2-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: layoutlmv2-base-uncased_finetuned_docvqa_v2 |
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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-base-uncased_finetuned_docvqa_v2 |
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4977 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 5.1316 | 0.44 | 50 | 4.3296 | |
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| 4.3071 | 0.88 | 100 | 3.9311 | |
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| 3.8545 | 1.33 | 150 | 3.7061 | |
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| 3.6578 | 1.77 | 200 | 3.5642 | |
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| 3.2506 | 2.21 | 250 | 3.3789 | |
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| 2.9991 | 2.65 | 300 | 3.1969 | |
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| 2.7893 | 3.1 | 350 | 3.2842 | |
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| 2.3975 | 3.54 | 400 | 2.8765 | |
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| 2.1188 | 3.98 | 450 | 3.0513 | |
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| 1.9405 | 4.42 | 500 | 2.6575 | |
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| 1.7123 | 4.87 | 550 | 2.8113 | |
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| 1.6361 | 5.31 | 600 | 2.6848 | |
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| 1.5425 | 5.75 | 650 | 2.7986 | |
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| 1.2871 | 6.19 | 700 | 2.9508 | |
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| 1.1132 | 6.64 | 750 | 2.7070 | |
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| 1.1105 | 7.08 | 800 | 2.6293 | |
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| 0.8855 | 7.52 | 850 | 2.9005 | |
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| 0.9427 | 7.96 | 900 | 2.4977 | |
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| 0.8359 | 8.41 | 950 | 2.7100 | |
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| 0.7038 | 8.85 | 1000 | 2.8090 | |
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| 0.7068 | 9.29 | 1050 | 2.8265 | |
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| 0.7037 | 9.73 | 1100 | 2.8136 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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