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layoutlm-funsd

Token Classification
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layoutlm
Generated from Trainer
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Files changed (11) hide show
  1. README.md +79 -0
  2. config.json +44 -0
  3. logs/events.out.tfevents.1701215550.daruiruidekuailetong.local.70323.0 +3 -0
  4. logs/events.out.tfevents.1701215876.daruiruidekuailetong.local.70323.1 +3 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +14 -0
  7. special_tokens_map.json +37 -0
  8. tokenizer.json +0 -0
  9. tokenizer_config.json +80 -0
  10. training_args.bin +3 -0
  11. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ base_model: microsoft/layoutlm-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - funsd
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+ model-index:
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+ - name: layoutlm-funsd
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+ results: []
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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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+ # layoutlm-funsd
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+
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+ This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Answer: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809}
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+ - Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
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+ - Question: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065}
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+ - Overall Precision: 0.0
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+ - Overall Recall: 0.0
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+ - Overall F1: 0.0
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+ - Overall Accuracy: 0.2750
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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+ - num_epochs: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------:|:-----------------------------------------------------------:|:------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 0.0 | 1.0 | 19 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 2.0 | 38 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 3.0 | 57 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 4.0 | 76 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 5.0 | 95 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 6.0 | 114 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 7.0 | 133 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 8.0 | 152 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 9.0 | 171 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 10.0 | 190 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 11.0 | 209 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 12.0 | 228 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 13.0 | 247 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 14.0 | 266 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+ | 0.0 | 15.0 | 285 | nan | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1065} | 0.0 | 0.0 | 0.0 | 0.2750 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.2.0.dev20231123
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "LayoutLMForTokenClassification"
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+ "3": "B-QUESTION",
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+ "max_2d_position_embeddings": 1024,
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+ "max_position_embeddings": 512,
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+ "model_type": "layoutlm",
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+ "num_attention_heads": 12,
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+ "output_past": true,
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+ {
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