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update model card README.md

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+ ---
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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-small-UnidicUnigram
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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-small-UnidicUnigram
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1279
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+ - Accuracy: 0.7455
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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: 0.0001
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+ - train_batch_size: 256
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 3
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+ - total_train_batch_size: 768
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+ - total_eval_batch_size: 24
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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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+ - lr_scheduler_warmup_ratio: 0.01
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+ - num_epochs: 14.0
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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 |
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+ |:-------------:|:-----:|:------:|:---------------:|:--------:|
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+ | 1.5872 | 1.0 | 69473 | 1.4531 | 0.6867 |
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+ | 1.4695 | 2.0 | 138946 | 1.3340 | 0.7073 |
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+ | 1.4136 | 3.0 | 208419 | 1.2793 | 0.7173 |
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+ | 1.3779 | 4.0 | 277892 | 1.2490 | 0.7227 |
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+ | 1.3546 | 5.0 | 347365 | 1.2227 | 0.7277 |
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+ | 1.3353 | 6.0 | 416838 | 1.2070 | 0.7307 |
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+ | 1.3182 | 7.0 | 486311 | 1.1895 | 0.7334 |
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+ | 1.3058 | 8.0 | 555784 | 1.1777 | 0.7360 |
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+ | 1.2974 | 9.0 | 625257 | 1.1660 | 0.7378 |
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+ | 1.2857 | 10.0 | 694730 | 1.1543 | 0.7401 |
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+ | 1.2755 | 11.0 | 764203 | 1.1514 | 0.7408 |
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+ | 1.2694 | 12.0 | 833676 | 1.1377 | 0.7431 |
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+ | 1.2623 | 13.0 | 903149 | 1.1338 | 0.7442 |
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+ | 1.2587 | 14.0 | 972622 | 1.1279 | 0.7455 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.12.0+cu116
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+ - Datasets 2.9.0
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+ - Tokenizers 0.12.1