Who knew the power of encoder only models?
Resources:
BERT Paper: https://arxiv.org/pdf/1810.04805
ModernBERT Blog: https://huggingface.co/blog/modernbert
Phillip Schmid Fine Tuning BERT: https://www.philschmid.de/fine-tune-modern-bert-in-2025
Fine Tuning Notebook: https://colab.research.google.com/drive/1G7oHp_8R4fmOSpjwaNB_T2NUJsmMh4Kw?usp=sharing
ModernBERT-Large-llm-router: https://huggingface.co/AdamLucek/ModernBERT-large-llm-router
Additional Readings
BERT Transformers, How Do They Work?: https://dzone.com/articles/bert-transformers-how-do-they-work
BERT Explained: https://towardsdatascience.com/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270
QnA With BERT: https://medium.com/analytics-vidhya/question-answering-system-with-bert-ebe1130f8def
BERT 101: https://huggingface.co/blog/bert-101
Paper Summary - BERT: https://medium.com/analytics-vidhya/paper-summary-bert-pre-training-of-deep-bidirectional-transformers-for-language-understanding-861456fed1f9
Chapters:
00:00 - Encoder vs Decoder Models
02:02 - Explanation: Overview
03:13 - Explanation: Attention
04:39 - Explanation: Masked Language Modelling & NSP
06:29 - Explanation: Benefits of BERT
07:28 - Explanation: Fine Tuning Variations
10:11 - Explanation: BERT vs GPT
11:54 - ModernBERT: The Next Gen BERT Model
15:10 - Fine Tuning: Overview
16:35 - Fine Tuning: Data Prep
20:49 - Fine Tuning: Model Prep
22:15 - Fine Tuning: Evaluation Metric
23:29 - Fine Tuning: Training
24:59 - Fine Tuning: Testing The Model
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