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layoutlmv3-finetuned-FUSND_1000

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README.md ADDED
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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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+ datasets:
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+ - funsd-layoutlmv3
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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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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: funsd-layoutlmv3
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+ type: funsd-layoutlmv3
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+ config: funsd
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+ split: test
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+ args: funsd
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.8808265257087938
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+ - name: Recall
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+ type: recall
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+ value: 0.910581222056632
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+ - name: F1
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+ type: f1
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+ value: 0.895456765999023
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8507072387970998
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+ ---
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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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+
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+ # test
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5799
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+ - Precision: 0.8808
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+ - Recall: 0.9106
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+ - F1: 0.8955
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+ - Accuracy: 0.8507
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - training_steps: 1000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.3333 | 100 | 0.6686 | 0.7452 | 0.8251 | 0.7831 | 0.7535 |
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+ | No log | 2.6667 | 200 | 0.4724 | 0.8064 | 0.8713 | 0.8376 | 0.8389 |
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+ | No log | 4.0 | 300 | 0.4922 | 0.8612 | 0.8942 | 0.8774 | 0.8481 |
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+ | No log | 5.3333 | 400 | 0.4632 | 0.8587 | 0.8997 | 0.8787 | 0.8521 |
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+ | 0.544 | 6.6667 | 500 | 0.4850 | 0.8632 | 0.9031 | 0.8827 | 0.8474 |
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+ | 0.544 | 8.0 | 600 | 0.5024 | 0.8744 | 0.8992 | 0.8866 | 0.8451 |
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+ | 0.544 | 9.3333 | 700 | 0.5394 | 0.8768 | 0.9155 | 0.8957 | 0.8565 |
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+ | 0.544 | 10.6667 | 800 | 0.5647 | 0.8800 | 0.9146 | 0.8970 | 0.8550 |
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+ | 0.544 | 12.0 | 900 | 0.5798 | 0.8847 | 0.9106 | 0.8974 | 0.8545 |
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+ | 0.1288 | 13.3333 | 1000 | 0.5799 | 0.8808 | 0.9106 | 0.8955 | 0.8507 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.1.1+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.19.1
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