End of training

README.md

@@ -0,0 +1,76 @@
+---
+license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutlmv3-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-large-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-large-cord
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1616
+- Precision: 0.9526
+- Recall: 0.9482
+- F1: 0.9504
+- Accuracy: 0.9677
+
+## 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: 2
+- eval_batch_size: 2
+- 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        | 0.25  | 100  | 0.5321          | 0.7584    | 0.7859 | 0.7719 | 0.8224   |
+| No log        | 0.5   | 200  | 0.4949          | 0.8091    | 0.8354 | 0.8221 | 0.8683   |
+| No log        | 0.75  | 300  | 0.3478          | 0.8668    | 0.8648 | 0.8658 | 0.8916   |
+| No log        | 1.0   | 400  | 0.5194          | 0.75      | 0.7117 | 0.7304 | 0.8513   |
+| 0.6065        | 1.25  | 500  | 0.3052          | 0.9059    | 0.9003 | 0.9031 | 0.9341   |
+| 0.6065        | 1.5   | 600  | 0.2427          | 0.9245    | 0.9173 | 0.9209 | 0.9443   |
+| 0.6065        | 1.75  | 700  | 0.2372          | 0.9174    | 0.9181 | 0.9177 | 0.9477   |
+| 0.6065        | 2.0   | 800  | 0.2044          | 0.9247    | 0.9212 | 0.9230 | 0.9494   |
+| 0.6065        | 2.25  | 900  | 0.1847          | 0.9442    | 0.9413 | 0.9427 | 0.9613   |
+| 0.1862        | 2.5   | 1000 | 0.1616          | 0.9526    | 0.9482 | 0.9504 | 0.9677   |
+
+
+### 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,