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thatdramebaazguy
/
roberta-base-MITmovie

Token Classification
Transformers
PyTorch
TensorFlow
JAX
roberta
roberta-base
NER
named-entities
BIO
movies
Inference Endpoints
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YAML Metadata Error: "datasets[0]" with value "MIT Movie" is not valid. If possible, use a dataset id from https://hf.co/datasets.
YAML Metadata Error: "language[0]" must only contain lowercase characters
YAML Metadata Error: "language[0]" with value "English" is not valid. It must be an ISO 639-1, 639-2 or 639-3 code (two/three letters), or a special value like "code", "multilingual". If you want to use BCP-47 identifiers, you can specify them in language_bcp47.

roberta-base + Movies NER Task

Objective: This is Roberta Base trained for the NER task using MIT Movie Dataset

model_name = "thatdramebaazguy/roberta-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 = 0.9476
  • eval_f1 = 0.8853
  • eval_loss = 0.2208
  • eval_mem_cpu_alloc_delta = 17MB
  • eval_mem_cpu_peaked_delta = 2MB
  • eval_mem_gpu_alloc_delta = 0MB
  • eval_mem_gpu_peaked_delta = 38MB
  • eval_precision = 0.8833
  • eval_recall = 0.8874
  • eval_runtime = 0:00:03.62
  • eval_samples = 1955

Github Repo:

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