End of training
Browse files- README.md +52 -0
- added_tokens.json +29 -0
- preprocessor_config.json +24 -0
- pytorch_model.bin +1 -1
- runs/Dec19_23-43-21_ip-10-160-32-10/events.out.tfevents.1671493413.ip-10-160-32-10.8938.0 +2 -2
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +43 -0
- tokenizer.json +0 -0
- tokenizer_config.json +21 -0
README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: ananth-docai4
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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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# ananth-docai4
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This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
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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: 2e-05
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- train_batch_size: 2
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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: 3
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.22.0
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- Pytorch 1.13.1+cu117
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- Datasets 2.7.1
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- Tokenizers 0.12.1
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added_tokens.json
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{
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"</s_Actual Cash Value Amount>": 57546,
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"</s_Balance Due Amount>": 57540,
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"</s_Contractor/Vendor Name>": 57532,
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"</s_Deductible Amount>": 57544,
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"</s_Depreciation Amount>": 57542,
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"</s_Invoice Date>": 57530,
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"</s_Invoice Number>": 57536,
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"</s_Invoice Total Amount>": 57528,
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"</s_Job Completed Date>": 57548,
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"</s_Permit Amount>": 57526,
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"</s_Policyholder Name>": 57534,
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"</s_Total Received/Down Payment>": 57538,
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"<s_Actual Cash Value Amount>": 57545,
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"<s_Balance Due Amount>": 57539,
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"<s_Contractor/Vendor Name>": 57531,
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"<s_Deductible Amount>": 57543,
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"<s_Depreciation Amount>": 57541,
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"<s_Invoice Date>": 57529,
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"<s_Invoice Number>": 57535,
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"<s_Invoice Total Amount>": 57527,
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"<s_Job Completed Date>": 57547,
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"<s_Permit Amount>": 57525,
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"<s_Policyholder Name>": 57533,
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"<s_Total Received/Down Payment>": 57537,
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"<s_iitcdip>": 57523,
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"<s_synthdog>": 57524,
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"<sep/>": 57522
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}
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preprocessor_config.json
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{
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"do_align_long_axis": false,
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"do_normalize": true,
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"do_pad": true,
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"do_resize": true,
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"do_thumbnail": true,
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"feature_extractor_type": "DonutFeatureExtractor",
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"processor_class": "DonutProcessor",
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"resample": 2,
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"size": [
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720,
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960
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]
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}
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pytorch_model.bin
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runs/Dec19_23-43-21_ip-10-160-32-10/events.out.tfevents.1671493413.ip-10-160-32-10.8938.0
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sentencepiece.bpe.model
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<s_Permit Amount>",
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"</s_Permit Amount>",
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"<s_Invoice Total Amount>",
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"</s_Invoice Total Amount>",
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"<s_Invoice Date>",
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"</s_Invoice Date>",
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"<s_Contractor/Vendor Name>",
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"</s_Contractor/Vendor Name>",
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"<s_Policyholder Name>",
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"</s_Policyholder Name>",
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"<s_Invoice Number>",
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"</s_Invoice Number>",
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"<s_Total Received/Down Payment>",
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"</s_Total Received/Down Payment>",
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"<s_Balance Due Amount>",
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"</s_Balance Due Amount>",
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"<s_Depreciation Amount>",
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"</s_Depreciation Amount>",
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"<s_Deductible Amount>",
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"</s_Deductible Amount>",
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"<s_Actual Cash Value Amount>",
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"</s_Actual Cash Value Amount>",
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"<s_Job Completed Date>",
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"</s_Job Completed Date>",
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"<s>",
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],
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"unk_token": "<unk>"
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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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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"name_or_path": "naver-clova-ix/donut-base",
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"pad_token": "<pad>",
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"processor_class": "DonutProcessor",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": null,
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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