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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-ap7_11_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-ap7_11_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: 0.0229
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+ - Precision: 0.9565
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+ - Recall: 0.7857
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+ - F1: 0.8627
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+ - Accuracy: 0.9975
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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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+ | 0.2919 | 50.0 | 250 | 0.0264 | 0.68 | 0.6071 | 0.6415 | 0.9963 |
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+ | 0.0045 | 100.0 | 500 | 0.0229 | 0.9565 | 0.7857 | 0.8627 | 0.9975 |
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+ | 0.0012 | 150.0 | 750 | 0.0282 | 0.7059 | 0.8571 | 0.7742 | 0.9961 |
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+ | 0.0008 | 200.0 | 1000 | 0.0244 | 0.8214 | 0.8214 | 0.8214 | 0.9970 |
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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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