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:
