Model save
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README.md
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---
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library_name: transformers
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license: mit
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base_model: naver-clova-ix/donut-base
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: donut-distinct
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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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# donut-distinct
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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 imagefolder 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: 3e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- training_steps: 70000
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.56.1
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- Pytorch 2.10.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"eos_token_id": 2,
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"forced_eos_token_id": 2,
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"pad_token_id": 1,
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"transformers_version": "4.56.1"
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}
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model.safetensors
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runs/May22_04-52-40_a2bf22e7defb/events.out.tfevents.1779425562.a2bf22e7defb.649.0
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size 88797
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