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Vineetttt/layoutlmv3-base-finetuned-FUNSD-dataset

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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: 0.8892100192678227
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+ - name: Recall
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+ type: recall
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+ value: 0.9170392449080974
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+ - name: F1
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+ type: f1
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+ value: 0.9029102470041576
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8690122429573279
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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: 0.5352
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+ - Precision: 0.8892
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+ - Recall: 0.9170
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+ - F1: 0.9029
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+ - Accuracy: 0.8690
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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 | 1.33 | 100 | 0.7740 | 0.7470 | 0.8127 | 0.7785 | 0.7037 |
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+ | No log | 2.67 | 200 | 0.5483 | 0.8111 | 0.8937 | 0.8504 | 0.7910 |
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+ | No log | 4.0 | 300 | 0.4411 | 0.8400 | 0.8813 | 0.8601 | 0.8492 |
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+ | No log | 5.33 | 400 | 0.4512 | 0.8432 | 0.8952 | 0.8684 | 0.8499 |
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+ | 0.5705 | 6.67 | 500 | 0.4541 | 0.8865 | 0.9195 | 0.9027 | 0.8652 |
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+ | 0.5705 | 8.0 | 600 | 0.4939 | 0.8782 | 0.9165 | 0.8969 | 0.8625 |
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+ | 0.5705 | 9.33 | 700 | 0.5152 | 0.8792 | 0.9151 | 0.8968 | 0.8572 |
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+ | 0.5705 | 10.67 | 800 | 0.5299 | 0.8856 | 0.9116 | 0.8984 | 0.8663 |
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+ | 0.5705 | 12.0 | 900 | 0.5162 | 0.8894 | 0.9185 | 0.9037 | 0.8697 |
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+ | 0.1324 | 13.33 | 1000 | 0.5352 | 0.8892 | 0.9170 | 0.9029 | 0.8690 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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