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by | Nov 12, 2022 | Machine Learning | 0 comments

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Please look at Instructions.png for further instructions, but in summary:
You will be designing and training a language model on the Penn Treebank and write a 1-2 page report on it (using the ACL stuff)
For the model, you can make use of
•RNN, LSTM, GRU, etc.
•Attention
•Different tokenizers
•Pretrained embeddings (word2vec, GloVe; note: you may NOT use any pretrained models or any external libraries to write your model and training/eval loops, such as those in huggingface or keras.
•Hyperparameter tuning
•Regularization, dropout, etc.
You’ll load the Penn Treebank using the load_dataset function as follows
from datasets import load_dataset
ptb = load_dataset(‘ptb_text_only’) # download the dataset

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