End of training

README.md

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+---
+license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutlmv3-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-cord
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# layoutlmv3-cord
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1589
+- Precision: 0.9433
+- Recall: 0.9521
+- F1: 0.9477
+- Accuracy: 0.9669
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.5   | 100  | 0.6487          | 0.7825    | 0.8006 | 0.7914 | 0.8330   |
+| No log        | 1.0   | 200  | 0.4266          | 0.8496    | 0.8686 | 0.8590 | 0.8925   |
+| No log        | 1.5   | 300  | 0.2553          | 0.9008    | 0.9057 | 0.9033 | 0.9341   |
+| No log        | 2.0   | 400  | 0.2496          | 0.8960    | 0.9057 | 0.9008 | 0.9295   |
+| 0.5667        | 2.5   | 500  | 0.2016          | 0.9274    | 0.9374 | 0.9324 | 0.9554   |
+| 0.5667        | 3.0   | 600  | 0.1806          | 0.9387    | 0.9467 | 0.9427 | 0.9609   |
+| 0.5667        | 3.5   | 700  | 0.1667          | 0.9424    | 0.9474 | 0.9449 | 0.9630   |
+| 0.5667        | 4.0   | 800  | 0.1735          | 0.9452    | 0.9467 | 0.9459 | 0.9639   |
+| 0.5667        | 4.5   | 900  | 0.1657          | 0.9456    | 0.9529 | 0.9492 | 0.9660   |
+| 0.1025        | 5.0   | 1000 | 0.1589          | 0.9433    | 0.9521 | 0.9477 | 0.9669   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.0
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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preprocessor_config.json

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 {
-  "apply_ocr": false,
+  "apply_ocr": true,
   "do_normalize": true,
   "do_rescale": true,
   "do_resize": true,