End of training

README.md

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+---
+license: mit
+base_model: SCUT-DLVCLab/lilt-roberta-en-base
+tags:
+- generated_from_trainer
+datasets:
+- funsd-layoutlmv3
+model-index:
+- name: lilt-en-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. -->
+
+# lilt-en-funsd
+
+This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the funsd-layoutlmv3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2946
+- Answer: {'precision': 0.8767772511848341, 'recall': 0.9057527539779682, 'f1': 0.8910295003010236, 'number': 817}
+- Header: {'precision': 0.6106194690265486, 'recall': 0.5798319327731093, 'f1': 0.5948275862068966, 'number': 119}
+- Question: {'precision': 0.885766092475068, 'recall': 0.9071494893221913, 'f1': 0.8963302752293578, 'number': 1077}
+- Overall Precision: 0.8670
+- Overall Recall: 0.8872
+- Overall F1: 0.8770
+- Overall Accuracy: 0.8038
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.3
+- Tokenizers 0.13.3

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preprocessor_config.json

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+  "apply_ocr": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
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+  "image_processor_type": "LayoutLMv3FeatureExtractor",
+  "image_std": [
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+  "ocr_lang": null,
+  "processor_class": "LayoutLMv3Processor",
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+  "size": {
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+    "width": 224
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+  "tesseract_config": ""
+}

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