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OCR-LayoutLMv3

Token Classification
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layoutlmv3
Generated from Trainer
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  1. README.md +108 -0
  2. logs/events.out.tfevents.1667612186.158-101-127-87.64910.0 +2 -2
  3. pytorch_model.bin +1 -1
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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+ datasets:
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+ - funsd-layoutlmv3
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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: OCR-LayoutLMv3
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: funsd-layoutlmv3
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+ type: funsd-layoutlmv3
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+ config: funsd
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+ split: train
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+ args: funsd
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.8988653182042428
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+ - name: Recall
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+ type: recall
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+ value: 0.905116741182315
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+ - name: F1
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+ type: f1
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+ value: 0.9019801980198019
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8403661000832046
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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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+ # OCR-LayoutLMv3
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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 funsd-layoutlmv3 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9788
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+ - Precision: 0.8989
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+ - Recall: 0.9051
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+ - F1: 0.9020
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+ - Accuracy: 0.8404
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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: 2000
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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 | 1.33 | 100 | 0.6966 | 0.7418 | 0.8063 | 0.7727 | 0.7801 |
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+ | No log | 2.67 | 200 | 0.5767 | 0.8104 | 0.8644 | 0.8365 | 0.8117 |
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+ | No log | 4.0 | 300 | 0.5355 | 0.8246 | 0.8852 | 0.8539 | 0.8295 |
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+ | No log | 5.33 | 400 | 0.5240 | 0.8706 | 0.8922 | 0.8813 | 0.8427 |
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+ | 0.5326 | 6.67 | 500 | 0.6337 | 0.8528 | 0.8778 | 0.8651 | 0.8260 |
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+ | 0.5326 | 8.0 | 600 | 0.6870 | 0.8698 | 0.8828 | 0.8762 | 0.8240 |
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+ | 0.5326 | 9.33 | 700 | 0.6584 | 0.8723 | 0.9061 | 0.8889 | 0.8342 |
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+ | 0.5326 | 10.67 | 800 | 0.7186 | 0.8868 | 0.9031 | 0.8949 | 0.8335 |
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+ | 0.5326 | 12.0 | 900 | 0.6822 | 0.9040 | 0.9076 | 0.9058 | 0.8526 |
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+ | 0.1248 | 13.33 | 1000 | 0.7042 | 0.8872 | 0.9021 | 0.8946 | 0.8511 |
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+ | 0.1248 | 14.67 | 1100 | 0.7920 | 0.9027 | 0.9036 | 0.9032 | 0.8480 |
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+ | 0.1248 | 16.0 | 1200 | 0.8052 | 0.8964 | 0.9151 | 0.9056 | 0.8389 |
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+ | 0.1248 | 17.33 | 1300 | 0.8932 | 0.8995 | 0.9066 | 0.9030 | 0.8329 |
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+ | 0.1248 | 18.67 | 1400 | 0.8728 | 0.8950 | 0.9061 | 0.9005 | 0.8398 |
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+ | 0.0442 | 20.0 | 1500 | 0.9051 | 0.8960 | 0.9116 | 0.9037 | 0.8347 |
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+ | 0.0442 | 21.33 | 1600 | 0.9587 | 0.8947 | 0.9031 | 0.8989 | 0.8401 |
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+ | 0.0442 | 22.67 | 1700 | 0.9822 | 0.9042 | 0.9046 | 0.9044 | 0.8389 |
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+ | 0.0442 | 24.0 | 1800 | 0.9734 | 0.9043 | 0.9061 | 0.9052 | 0.8391 |
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+ | 0.0442 | 25.33 | 1900 | 0.9842 | 0.9042 | 0.9091 | 0.9066 | 0.8410 |
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+ | 0.0225 | 26.67 | 2000 | 0.9788 | 0.8989 | 0.9051 | 0.9020 | 0.8404 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.0.dev0
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+ - Pytorch 1.12.1
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+ - Datasets 2.6.1
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+ - Tokenizers 0.13.1
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