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Movie Roberta + Movies NER Task

Objective: This is Roberta Base + Movie DAPT --> trained for the NER task using MIT Movie Dataset https://huggingface.co/thatdramebaazguy/movie-roberta-base was used as the MovieRoberta.

model_name = "thatdramebaazguy/movie-roberta-MITmovieroberta-base-MITmovie"
pipeline(model=model_name, tokenizer=model_name, revision="v1.0", task="ner")

Overview

Language model: roberta-base
Language: English
Downstream-task: NER
Training data: MIT Movie
Eval data: MIT Movie
Infrastructure: 2x Tesla v100
Code: See example

Hyperparameters

Num examples = 6253  
Num Epochs = 5 
Instantaneous batch size per device = 64
Total train batch size (w. parallel, distributed & accumulation) = 128  

Performance

Eval on MIT Movie

  • epoch = 5.0
  • eval_accuracy = 0.9472
  • eval_f1 = 0.8876
  • eval_loss = 0.2211
  • eval_mem_cpu_alloc_delta = 3MB
  • eval_mem_cpu_peaked_delta = 2MB
  • eval_mem_gpu_alloc_delta = 0MB
  • eval_mem_gpu_peaked_delta = 38MB
  • eval_precision = 0.887
  • eval_recall = 0.8881
  • eval_runtime = 0:00:03.73
  • eval_samples = 1955
  • eval_samples_per_second = 523.095

Github Repo:


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Dataset used to train thatdramebaazguy/movie-roberta-MITmovie