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--- |
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language: en |
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thumbnail: https://huggingface.co/front/thumbnails/google.png |
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license: apache-2.0 |
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base_model: |
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- google/mobilebert-uncased |
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pipeline_tag: text-classification |
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library_name: transformers |
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metrics: |
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- f1 |
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- precision |
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- recall |
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--- |
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## MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices |
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MobileBERT is a thin version of BERT_LARGE, while equipped with bottleneck structures and a carefully designed balance |
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between self-attentions and feed-forward networks. |
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This checkpoint is the original MobileBert Optimized Uncased English: |
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[uncased_L-24_H-128_B-512_A-4_F-4_OPT](https://storage.googleapis.com/cloud-tpu-checkpoints/mobilebert/uncased_L-24_H-128_B-512_A-4_F-4_OPT.tar.gz) |
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checkpoint. |
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This model was fine-tuned on html tags and labels using [Fathom](https://mozilla.github.io/fathom/commands/label.html). |
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## How to use MobileBERT in `transformers` |
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```python |
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from transformers import pipeline |
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classifier = pipeline( |
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"text-classification", |
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model="vazish/mobile_bert_autofill", |
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tokenizer="vazish/mobile_bert_autofill" |
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) |
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print( |
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classifier('<input class="cc-number" placeholder="Enter credit card number..." />') |
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) |
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``` |
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## Model Training Info |
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```python |
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HyperParameters: { |
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'learning_rate': 0.000082, |
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'num_train_epochs': 12, |
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'weight_decay': 0.1, |
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'per_device_train_batch_size': 32, |
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} |
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``` |
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# Model Performance |
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``` |
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Test Performance: |
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Precision: 0.97043 |
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Recall: 0.96966 |
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F1: 0.96921 |
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precision recall f1-score support |
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CC Expiration 1.000 0.875 0.933 16 |
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CC Expiration Month 1.000 0.972 0.986 36 |
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CC Expiration Year 0.973 0.973 0.973 37 |
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CC Name 1.000 0.968 0.984 31 |
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CC Number 0.942 0.980 0.961 50 |
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CC Payment Type 0.934 0.760 0.838 75 |
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CC Security Code 0.929 0.951 0.940 41 |
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CC Type 0.857 0.857 0.857 14 |
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Confirm Password 1.000 0.860 0.925 57 |
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Email 0.972 0.945 0.958 73 |
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First Name 0.833 1.000 0.909 5 |
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Form 0.950 0.974 0.962 39 |
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Last Name 0.833 1.000 0.909 5 |
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New Password 0.915 1.000 0.956 97 |
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Other 0.981 0.989 0.985 1235 |
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Phone 0.600 1.000 0.750 3 |
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Zip Code 0.939 0.969 0.954 32 |
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accuracy 0.970 1846 |
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macro avg 0.921 0.945 0.928 1846 |
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weighted avg 0.970 0.970 0.969 1846 |
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``` |