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aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616 aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616
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Contributed by

aodiniz Adriano Orsoni Diniz
35 models

How to use this model directly from the 🤗/transformers library:

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from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616") model = AutoModelWithLMHead.from_pretrained("aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616")

BERT L-10 H-512 fine-tuned on MLM (CORD-19 2020/06/16)

BERT model with 10 Transformer layers and hidden embedding of size 512, referenced in Well-Read Students Learn Better: On the Importance of Pre-training Compact Models, fine-tuned for MLM on CORD-19 dataset (as released on 2020/06/16).

Training the model

    --model_type bert
    --model_name_or_path google/bert_uncased_L-10_H-512_A-8
    --train_data_file {cord19-200616-dataset}
    --mlm_probability 0.2
    --block_size 512
    --per_device_train_batch_size 10
    --learning_rate 3e-5
    --num_train_epochs 2
    --output_dir bert_uncased_L-10_H-512_A-8_cord19-200616