dwitidibyajyoti commited on
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End of training

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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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+ 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: layoutmlv3_thursday_oct_7_v5
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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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+ # layoutmlv3_thursday_oct_7_v5
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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: 0.1171
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+ - Precision: 0.8763
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+ - Recall: 0.9075
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+ - F1: 0.8916
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+ - Accuracy: 0.9821
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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 | 0.86 | 100 | 0.2961 | 0.8166 | 0.8559 | 0.8358 | 0.9372 |
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+ | No log | 1.72 | 200 | 0.1481 | 0.8037 | 0.8594 | 0.8306 | 0.9674 |
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+ | No log | 2.59 | 300 | 0.1191 | 0.8082 | 0.8772 | 0.8413 | 0.9753 |
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+ | No log | 3.45 | 400 | 0.0892 | 0.8969 | 0.9128 | 0.9048 | 0.9844 |
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+ | 0.29 | 4.31 | 500 | 0.1171 | 0.8763 | 0.9075 | 0.8916 | 0.9821 |
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+ | 0.29 | 5.17 | 600 | 0.0994 | 0.8864 | 0.9021 | 0.8942 | 0.9818 |
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+ | 0.29 | 6.03 | 700 | 0.0851 | 0.8901 | 0.8932 | 0.8917 | 0.9844 |
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+ | 0.29 | 6.9 | 800 | 0.0957 | 0.8425 | 0.8950 | 0.8680 | 0.9814 |
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+ | 0.29 | 7.76 | 900 | 0.0951 | 0.8735 | 0.8968 | 0.8850 | 0.9834 |
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+ | 0.1351 | 8.62 | 1000 | 0.1005 | 0.8772 | 0.9021 | 0.8895 | 0.9840 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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