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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/bert_uncased_L-4_H-128_A-2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert_uncased_L-4_H-128_A-2-OCR-quality-classification-cls
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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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+ # bert_uncased_L-4_H-128_A-2-OCR-quality-classification-cls
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+
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+ This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0422
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+ - Accuracy: 0.99
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+ - Num Input Tokens Seen: 57341952
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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: 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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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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+ - optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 2.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
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+ | 0.1123 | 0.2660 | 250 | 0.1202 | 0.974 | 8192000 |
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+ | 0.072 | 0.5321 | 500 | 0.0665 | 0.986 | 16384000 |
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+ | 0.0404 | 0.7981 | 750 | 0.0464 | 0.988 | 24576000 |
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+ | 0.0255 | 1.0641 | 1000 | 0.0428 | 0.99 | 32765952 |
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+ | 0.0253 | 1.3301 | 1250 | 0.0357 | 0.99 | 40957952 |
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+ | 0.0329 | 1.5962 | 1500 | 0.0438 | 0.986 | 49149952 |
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+ | 0.0435 | 1.8622 | 1750 | 0.0422 | 0.99 | 57341952 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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