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README.md

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@@ -757,7 +757,7 @@ An example on how to use this class is given in the [`extract_features.py`](./ex
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- the masked language modeling logits, and
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- the next sentence classification logits.
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An example on how to use this class is given in the [`run_lm_finetuning.py`](./examples/run_lm_finetuning.py) script which can be used to fine-tune the BERT language model on your specific different text corpus. This should improve model performance, if the language style is different from the original BERT training corpus (Wiki + BookCorpus).
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There are two examples on how to use this class is given in the [`lm_finetuning/`](./examples/lm_finetuning/) directory. The scripts in this directory can be used to fine-tune the BERT language model. This should improve model performance, if the language style is different from the original BERT training corpus (Wiki + BookCorpus).
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#### 3. `BertForMaskedLM`
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| Sub-section | Description |
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|-|-|
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| [Training large models: introduction, tools and examples](#Training-large-models-introduction,-tools-and-examples) | How to use gradient-accumulation, multi-gpu training, distributed training, optimize on CPU and 16-bits training to train Bert models |
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| [Fine-tuning with BERT: running the examples](#Fine-tuning-with-BERT-running-the-examples) | Running the examples in [`./examples`](./examples/): `extract_classif.py`, `run_classifier.py`, `run_squad.py` and `run_lm_finetuning.py` |
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| [Fine-tuning with BERT: running the examples](#Fine-tuning-with-BERT-running-the-examples) | Running the examples in [`./examples`](./examples/): `extract_classif.py`, `run_classifier.py`, `run_squad.py` and `lm_finetuning/simple_lm_finetuning.py` |
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| [Fine-tuning with OpenAI GPT, Transformer-XL and GPT-2](#openai-gpt-transformer-xl-and-gpt-2-running-the-examples) | Running the examples in [`./examples`](./examples/): `run_openai_gpt.py`, `run_transfo_xl.py` and `run_gpt2.py` |
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| [Fine-tuning BERT-large on GPUs](#Fine-tuning-BERT-large-on-GPUs) | How to fine tune `BERT large`|
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