thatdramebaazguy/movie-roberta-MITmovie-squad

roberta-base + DAPT + Task Transfer for Domain-Specific QA

Objective: This is Roberta Base with Domain Adaptive Pretraining on Movie Corpora --> Then trained for the NER task using MIT Movie Dataset --> Then a changed head to do the SQuAD Task. This makes a QA model capable of answering questions in the movie domain, with additional information coming from a different task (NER - Task Transfer). https://huggingface.co/thatdramebaazguy/movie-roberta-base was used as the MovieRoberta.

model_name = "thatdramebaazguy/movie-roberta-MITmovie-squad"
pipeline(model=model_name, tokenizer=model_name, revision="v1.0", task="question-answering")

Overview

Language model: roberta-base Language: English Downstream-task: NER --> QA Training data: imdb, polarity movie data, cornellmoviedialogue, 25mlens movie names, MIT Movie, SQuADv1 Eval data: MoviesQA (From https://github.com/ibm-aur-nlp/domain-specific-QA) Infrastructure: 4x Tesla v100 Code: See example

Hyperparameters

Num examples = 88567  
Num Epochs = 3  
Instantaneous batch size per device = 32  
Total train batch size (w. parallel, distributed & accumulation) = 128  

Performance

Eval on SQuADv1

• —eval_samples = 10790
• —exact_match = 83.0274
• —f1 = 90.1615

Eval on MoviesQA

• —eval_samples = 5032
• —exact_match = 51.64944
• —f1 = 65.53983

Github Repo:

• —Domain-Adaptation Project