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End of training

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README.md CHANGED
@@ -1,10 +1,13 @@
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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-sroie-test
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  results: []
@@ -15,7 +18,17 @@ should probably proofread and complete it, then remove this comment. -->
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  # donut-base-sroie-test
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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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@@ -35,16 +48,30 @@ More information needed
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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: 32
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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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  ---
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  license: mit
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+ base_model: davelotito/donut-base-sroie-test
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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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+ metrics:
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+ - bleu
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+ - wer
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  model-index:
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  - name: donut-base-sroie-test
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  results: []
 
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  # donut-base-sroie-test
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+ This model is a fine-tuned version of [davelotito/donut-base-sroie-test](https://huggingface.co/davelotito/donut-base-sroie-test) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3913
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+ - Bleu: 0.0706
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+ - Precisions: [0.8125, 0.7440860215053764, 0.7064676616915423, 0.6637168141592921]
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+ - Brevity Penalty: 0.0968
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+ - Length Ratio: 0.2998
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+ - Translation Length: 528
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+ - Reference Length: 1761
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+ - Cer: 0.7448
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+ - Wer: 0.8259
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  ## Model description
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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: 4
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+ - eval_batch_size: 4
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
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+ | No log | 0.99 | 62 | 0.5515 | 0.0638 | [0.7647058823529411, 0.6831896551724138, 0.6309226932668329, 0.5857988165680473] | 0.0962 | 0.2993 | 527 | 1761 | 0.7627 | 0.8549 |
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+ | 0.5624 | 2.0 | 125 | 0.4773 | 0.0665 | [0.7763157894736842, 0.6865671641791045, 0.6403940886699507, 0.5918367346938775] | 0.0992 | 0.3021 | 532 | 1761 | 0.7562 | 0.8390 |
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+ | 0.5624 | 2.99 | 187 | 0.4273 | 0.0658 | [0.7840909090909091, 0.6903225806451613, 0.6517412935323383, 0.6047197640117994] | 0.0968 | 0.2998 | 528 | 1761 | 0.7513 | 0.8373 |
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+ | 0.2964 | 4.0 | 250 | 0.4007 | 0.0679 | [0.800376647834275, 0.7072649572649573, 0.6592592592592592, 0.6023391812865497] | 0.0986 | 0.3015 | 531 | 1761 | 0.7478 | 0.8286 |
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+ | 0.2238 | 4.99 | 312 | 0.3965 | 0.0710 | [0.8142589118198874, 0.7297872340425532, 0.683046683046683, 0.6308139534883721] | 0.0999 | 0.3027 | 533 | 1761 | 0.7427 | 0.8271 |
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+ | 0.2238 | 6.0 | 375 | 0.3939 | 0.0719 | [0.8301886792452831, 0.7537473233404711, 0.7054455445544554, 0.656891495601173] | 0.0980 | 0.3010 | 530 | 1761 | 0.7414 | 0.8246 |
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+ | 0.147 | 6.99 | 437 | 0.3853 | 0.0693 | [0.8159392789373814, 0.7370689655172413, 0.6932668329177057, 0.6449704142011834] | 0.0962 | 0.2993 | 527 | 1761 | 0.7437 | 0.8237 |
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+ | 0.1316 | 8.0 | 500 | 0.3827 | 0.0698 | [0.8037735849056604, 0.7301927194860813, 0.6856435643564357, 0.6392961876832844] | 0.0980 | 0.3010 | 530 | 1761 | 0.7456 | 0.8296 |
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+ | 0.1316 | 8.99 | 562 | 0.3895 | 0.0704 | [0.8174904942965779, 0.7516198704103672, 0.715, 0.6706231454005934] | 0.0956 | 0.2987 | 526 | 1761 | 0.7439 | 0.8259 |
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+ | 0.1153 | 9.92 | 620 | 0.3913 | 0.0706 | [0.8125, 0.7440860215053764, 0.7064676616915423, 0.6637168141592921] | 0.0968 | 0.2998 | 528 | 1761 | 0.7448 | 0.8259 |
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  ### Framework versions
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