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Output_LayoutLMv3_v5

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layoutlmv3
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  1. README.md +94 -0
  2. pytorch_model.bin +1 -1
  3. runs/Apr08_14-31-51_ip-10-192-12-213/events.out.tfevents.1712586740.ip-10-192-12-213.23658.4 +2 -2
README.md ADDED
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+ ---
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+ license: cc-by-nc-sa-4.0
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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: Output_LayoutLMv3_v8
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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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+ # Output_LayoutLMv3_v8
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3054
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+ - Precision: 0.8505
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+ - Recall: 0.8273
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+ - F1: 0.8387
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+ - Accuracy: 0.9723
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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-06
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+ - train_batch_size: 3
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+ - eval_batch_size: 3
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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: 3000
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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 | 2.38 | 100 | 0.2910 | 0.7636 | 0.7636 | 0.7636 | 0.9637 |
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+ | No log | 4.76 | 200 | 0.2822 | 0.8318 | 0.8091 | 0.8203 | 0.9706 |
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+ | No log | 7.14 | 300 | 0.2942 | 0.8148 | 0.8 | 0.8073 | 0.9689 |
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+ | No log | 9.52 | 400 | 0.2821 | 0.7909 | 0.7909 | 0.7909 | 0.9671 |
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+ | 0.0005 | 11.9 | 500 | 0.2896 | 0.7909 | 0.7909 | 0.7909 | 0.9671 |
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+ | 0.0005 | 14.29 | 600 | 0.2914 | 0.8241 | 0.8091 | 0.8165 | 0.9706 |
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+ | 0.0005 | 16.67 | 700 | 0.2912 | 0.8095 | 0.7727 | 0.7907 | 0.9689 |
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+ | 0.0005 | 19.05 | 800 | 0.2578 | 0.8241 | 0.8091 | 0.8165 | 0.9706 |
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+ | 0.0005 | 21.43 | 900 | 0.2830 | 0.8241 | 0.8091 | 0.8165 | 0.9706 |
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+ | 0.0005 | 23.81 | 1000 | 0.2878 | 0.8411 | 0.8182 | 0.8295 | 0.9723 |
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+ | 0.0005 | 26.19 | 1100 | 0.3151 | 0.8113 | 0.7818 | 0.7963 | 0.9689 |
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+ | 0.0005 | 28.57 | 1200 | 0.3142 | 0.7706 | 0.7636 | 0.7671 | 0.9637 |
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+ | 0.0005 | 30.95 | 1300 | 0.2972 | 0.8273 | 0.8273 | 0.8273 | 0.9723 |
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+ | 0.0005 | 33.33 | 1400 | 0.2866 | 0.8148 | 0.8 | 0.8073 | 0.9706 |
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+ | 0.0004 | 35.71 | 1500 | 0.2737 | 0.8288 | 0.8364 | 0.8326 | 0.9723 |
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+ | 0.0004 | 38.1 | 1600 | 0.2653 | 0.8532 | 0.8455 | 0.8493 | 0.9740 |
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+ | 0.0004 | 40.48 | 1700 | 0.2740 | 0.8108 | 0.8182 | 0.8145 | 0.9706 |
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+ | 0.0004 | 42.86 | 1800 | 0.2861 | 0.8198 | 0.8273 | 0.8235 | 0.9706 |
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+ | 0.0004 | 45.24 | 1900 | 0.2904 | 0.7788 | 0.8 | 0.7892 | 0.9671 |
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+ | 0.0004 | 47.62 | 2000 | 0.2899 | 0.7788 | 0.8 | 0.7892 | 0.9671 |
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+ | 0.0004 | 50.0 | 2100 | 0.2957 | 0.8108 | 0.8182 | 0.8145 | 0.9689 |
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+ | 0.0004 | 52.38 | 2200 | 0.2962 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0004 | 54.76 | 2300 | 0.2962 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0004 | 57.14 | 2400 | 0.3057 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0002 | 59.52 | 2500 | 0.3070 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0002 | 61.9 | 2600 | 0.3050 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0002 | 64.29 | 2700 | 0.3050 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0002 | 66.67 | 2800 | 0.3052 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0002 | 69.05 | 2900 | 0.3052 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+ | 0.0 | 71.43 | 3000 | 0.3054 | 0.8505 | 0.8273 | 0.8387 | 0.9723 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.13.3
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