Model Card for Model ID
DistilBERT NER - MIT Movie Trivia Dataset
This model is a fine-tuned version of DistilBERT (distilbert-base-uncased) on the MIT Movie Trivia Dataset for Named Entity Recognition (NER). It is designed to tag movie-related named entities such as actors, directors, characters, genres, and more.
Model Details
Base Model: DistilBERT (distilbert-base-uncased)
Dataset: MIT Movie Trivia NER Dataset
Fine-tuning Task: Named Entity Recognition (NER)
Framework: Hugging Face Transformers
Tokenizer: distilbert-base-uncased
Total Parameters: ~66M
Training Time: Approx. 8 epochs
Intended Use
This model is intended for Named Entity Recognition (NER) on movie-related text, such as:
Identifying actors, directors, characters, genres, release years, etc.
Extracting structured information from movie-related questions or reviews.
NER Labels (BIO Format)
The model uses the BIO (Beginning-Inside-Outside) format for labeling:
Tag Description
B-Actor Beginning of an actor's name
I-Actor Inside an actor's name
B-Director Beginning of a director's name
I-Director Inside a director's name
B-Character_Name Beginning of a character's name
I-Character_Name Inside a character's name
B-Genre Beginning of a genre
I-Genre Inside a genre
B-Year Movie release year
B-Plot Beginning of a plot description
I-Plot Inside a plot description
B-Quote Beginning of a movie quote
I-Quote Inside a movie quote
O Outside any named entity
Model Description
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Training Details
Training Details
Optimizer: AdamW
Learning Rate: 2e-5
Batch Size: 8
Evaluation Strategy: Epoch-based
Loss Function: CrossEntropyLoss
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Evaluation
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Results
Which movies did Quentin Tarantino make??
Ans: Entity: quentin tarantino, Label: Director, Score: 1.00
Leonardo DiCaprio starred in which movies?
Ans: Entity: leonardo dicaprio, Label: Actor, Score: 1.00
Summary
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