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-funsd
+  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-funsd
+
+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: 0.8190
+- Precision: 0.8973
+- Recall: 0.9111
+- F1: 0.9041
+- Accuracy: 0.8473
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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        | 5.26  | 100  | 0.5958          | 0.8295    | 0.8723 | 0.8504 | 0.8178   |
+| No log        | 10.53 | 200  | 0.6181          | 0.8505    | 0.8932 | 0.8713 | 0.8241   |
+| No log        | 15.79 | 300  | 0.6992          | 0.8841    | 0.9021 | 0.8930 | 0.8470   |
+| No log        | 21.05 | 400  | 0.8182          | 0.8931    | 0.9006 | 0.8969 | 0.8328   |
+| 0.3071        | 26.32 | 500  | 0.8190          | 0.8973    | 0.9111 | 0.9041 | 0.8473   |
+| 0.3071        | 31.58 | 600  | 0.9001          | 0.8812    | 0.9061 | 0.8935 | 0.8326   |
+| 0.3071        | 36.84 | 700  | 0.9112          | 0.8958    | 0.9101 | 0.9029 | 0.8435   |
+| 0.3071        | 42.11 | 800  | 0.9196          | 0.8951    | 0.9026 | 0.8988 | 0.8408   |
+| 0.3071        | 47.37 | 900  | 0.9256          | 0.8990    | 0.9061 | 0.9025 | 0.8454   |
+| 0.0245        | 52.63 | 1000 | 0.9584          | 0.8962    | 0.9046 | 0.9004 | 0.8431   |
+
+
+### 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": true,
   "do_normalize": true,
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   "do_resize": true,

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