End of training
Browse files- README.md +62 -0
- model.safetensors +1 -1
- preprocessor_config.json +14 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +80 -0
- vocab.txt +0 -0
README.md
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---
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license: mit
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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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model-index:
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- name: layoutlmv3-custom_no_text
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results: []
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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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# layoutlmv3-custom_no_text
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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 None dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.3487
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- eval_noise: {'precision': 0.6914893617021277, 'recall': 0.7210776545166403, 'f1': 0.7059736229635376, 'number': 631}
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- eval_signal: {'precision': 0.684931506849315, 'recall': 0.7142857142857143, 'f1': 0.6993006993006993, 'number': 630}
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- eval_overall_precision: 0.6882
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- eval_overall_recall: 0.7177
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- eval_overall_f1: 0.7026
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- eval_overall_accuracy: 0.9325
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- eval_runtime: 0.9604
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- eval_samples_per_second: 37.484
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- eval_steps_per_second: 5.206
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- epoch: 24.0
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- step: 432
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-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: 50
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 440686560
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version https://git-lfs.github.com/spec/v1
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oid sha256:e699f22b213a95ca4a10e4009b12962a035b6b6e27a1b5b8e443788bc4e5d856
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size 440686560
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preprocessor_config.json
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{
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"apply_ocr": false,
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"do_resize": true,
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"feature_extractor_type": "LayoutLMv2FeatureExtractor",
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"image_processor_type": "LayoutLMv2ImageProcessor",
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"ocr_lang": null,
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"processor_class": "LayoutLMv2Processor",
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"resample": 2,
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"size": {
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"height": 224,
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"width": 224
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},
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"tesseract_config": ""
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}
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special_tokens_map.json
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{
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"cls_token": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"sep_token": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [],
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"apply_ocr": false,
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"cls_token_box": [
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0,
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],
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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"only_label_first_subword": true,
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"pad_token": "[PAD]",
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"pad_token_box": [
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0,
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0,
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],
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"pad_token_label": -100,
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"processor_class": "LayoutLMv2Processor",
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"sep_token": "[SEP]",
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"sep_token_box": [
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1000,
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1000,
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1000,
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1000
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],
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "LayoutLMv2Tokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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