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layoutlmv1-er-ner

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layoutlm
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+ ---
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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: layoutlmv1-er-ner
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+ results: []
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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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+ # layoutlmv1-er-ner
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+
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+ This model is a fine-tuned version of [renjithks/layoutlmv1-cord-ner](https://huggingface.co/renjithks/layoutlmv1-cord-ner) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2936
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+ - Precision: 0.6097
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+ - Recall: 0.6192
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+ - F1: 0.6144
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+ - Accuracy: 0.9479
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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: 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: 20
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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 | 1.0 | 22 | 0.3856 | 0.3047 | 0.1453 | 0.1968 | 0.8885 |
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+ | No log | 2.0 | 44 | 0.2637 | 0.3725 | 0.3625 | 0.3674 | 0.9197 |
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+ | No log | 3.0 | 66 | 0.2184 | 0.5117 | 0.4612 | 0.4852 | 0.9361 |
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+ | No log | 4.0 | 88 | 0.2321 | 0.4714 | 0.5585 | 0.5113 | 0.9361 |
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+ | No log | 5.0 | 110 | 0.2183 | 0.5453 | 0.5853 | 0.5646 | 0.9440 |
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+ | No log | 6.0 | 132 | 0.2243 | 0.5977 | 0.5867 | 0.5922 | 0.9459 |
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+ | No log | 7.0 | 154 | 0.2451 | 0.5716 | 0.5910 | 0.5811 | 0.9410 |
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+ | No log | 8.0 | 176 | 0.2387 | 0.5881 | 0.5839 | 0.5860 | 0.9474 |
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+ | No log | 9.0 | 198 | 0.2702 | 0.5794 | 0.6023 | 0.5906 | 0.9430 |
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+ | No log | 10.0 | 220 | 0.2450 | 0.5920 | 0.6079 | 0.5999 | 0.9480 |
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+ | No log | 11.0 | 242 | 0.2697 | 0.6151 | 0.5994 | 0.6071 | 0.9467 |
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+ | No log | 12.0 | 264 | 0.2607 | 0.6022 | 0.6234 | 0.6126 | 0.9497 |
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+ | No log | 13.0 | 286 | 0.2737 | 0.6172 | 0.6276 | 0.6224 | 0.9488 |
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+ | No log | 14.0 | 308 | 0.2840 | 0.6117 | 0.6333 | 0.6223 | 0.9474 |
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+ | No log | 15.0 | 330 | 0.2833 | 0.6030 | 0.6192 | 0.6110 | 0.9476 |
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+ | No log | 16.0 | 352 | 0.3009 | 0.6161 | 0.6135 | 0.6148 | 0.9449 |
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+ | No log | 17.0 | 374 | 0.2920 | 0.6098 | 0.6150 | 0.6124 | 0.9473 |
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+ | No log | 18.0 | 396 | 0.2931 | 0.6017 | 0.6135 | 0.6075 | 0.9471 |
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+ | No log | 19.0 | 418 | 0.2935 | 0.6103 | 0.6206 | 0.6154 | 0.9476 |
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+ | No log | 20.0 | 440 | 0.2936 | 0.6097 | 0.6192 | 0.6144 | 0.9479 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1