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End of training

Browse files
README.md ADDED
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+ ---
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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-base-ner_small_memory
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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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+ # donut-base-ner_small_memory
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+
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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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+
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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: 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: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "<s_hs_code>",
285
+ "</s_origin_country>",
286
+ "<s_item_value>",
287
+ "</s_hs_code>",
288
+ "<s_net_weight>",
289
+ "<s>",
290
+ "<s_item_quantity>",
291
+ "</s_description>",
292
+ "<s_origin_country>",
293
+ "<s_gross_weight>",
294
+ "</s_net_weight>",
295
+ "<s_uom>",
296
+ "</s_item_value>",
297
+ "</s_uom>",
298
+ "<s_purchase_order>",
299
+ "<s_description>",
300
+ "<s_serial_number>",
301
+ "</s>",
302
+ "<s_total_item_value>",
303
+ "</s_serial_number>",
304
+ "<s_item_index>"
305
+ ],
306
+ "bos_token": "<s>",
307
+ "clean_up_tokenization_spaces": true,
308
+ "cls_token": "<s>",
309
+ "eos_token": "</s>",
310
+ "mask_token": "<mask>",
311
+ "model_max_length": 1000000000000000019884624838656,
312
+ "pad_token": "<pad>",
313
+ "processor_class": "DonutProcessor",
314
+ "sep_token": "</s>",
315
+ "sp_model_kwargs": {},
316
+ "tokenizer_class": "XLMRobertaTokenizer",
317
+ "unk_token": "<unk>"
318
+ }