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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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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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+ 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: layoutlmv3-ap8_1_stitched_16_batch_4e5
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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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+ # layoutlmv3-ap8_1_stitched_16_batch_4e5
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2170
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+ - Precision: 0.4419
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+ - Recall: 0.2
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+ - F1: 0.2754
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+ - Accuracy: 0.9807
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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: 4e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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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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+ | 0.0824 | 31.25 | 250 | 0.2011 | 0.2941 | 0.1579 | 0.2055 | 0.9794 |
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+ | 0.0061 | 62.5 | 500 | 0.2170 | 0.4419 | 0.2 | 0.2754 | 0.9807 |
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+ | 0.0015 | 93.75 | 750 | 0.2292 | 0.3469 | 0.1789 | 0.2361 | 0.9792 |
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+ | 0.001 | 125.0 | 1000 | 0.2334 | 0.3913 | 0.1895 | 0.2553 | 0.9797 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.4.1
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+ - Tokenizers 0.21.1
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