ahmeddeldalyyy/meeting-summarizer-meetingbank

Meeting Summarizer - Fine-tuned on MeetingBank

This model was fine-tuned on the MeetingBank dataset to generate concise summaries of meeting transcripts.

Performance

Metric	Validation	Test
ROUGE-1	49.99	49.26
ROUGE-2	37.42	37.07
ROUGE-L	45.45	45.01
ROUGE-Lsum	46.86	46.30

Usage

from transformers import pipeline

summarizer = pipeline("summarization", model="ahmeddeldalyyy/meeting-summarizer-meetingbank")
meeting_transcript = """
[Your meeting transcript here]
"""

summary = summarizer(meeting_transcript, max_length=142, min_length=56, num_beams=4, length_penalty=2.0)
print(summary[0]['summary_text'])

Model Details

• Base model: BART
• Fine-tuned on: MeetingBank dataset (city council meetings)
• Parameters:
  • max_input_length: 1,024 tokens
  • min_output_length: 56 tokens
  • max_output_length: 142 tokens
  • beam width: 4
  • length penalty: 2.0
  • learning rate: 2.5e-6
  • trained for 2 epochs