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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - knkarthick/dialogsum
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+ language:
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+ - en
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+ metrics:
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+ - rouge
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+ base_model:
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+ - google/flan-t5-small
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+ tags:
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+ - t5
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+ - flan
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+ - fine-tuned
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+ - instruction
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+ ---
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+
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+ # FLAN-T5-small Dialogue Summarization
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+
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+ ## Model Description
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+ Fine-tuned **FLAN-T5-small** model for dialogue summarization tasks using the DialogSum dataset. Achieves improved performance in generating concise summaries from conversational dialogues.
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+
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+ ## Training Data
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+ - **Dataset**: DialogSum (1,837 annotated dialogues)
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+ - **Preprocessing**: prompt_template = """
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+ Here is a dialogue:
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+ {dialogue}
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+ Write a short summary.
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+ {summary}
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+ """
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+
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+ Converted original dataset into instruction format with dialogue-summary pairs
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+
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+ ## Training Setup
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+ | Parameter | Value |
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+ |-----------|-------|
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+ | Base Model | google/flan-t5-small |
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+ | Epochs | 5 |
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+ | Batch Size | 16 (per device) |
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+ | Learning Rate | 3e-4 |
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+ | Optimizer | Adafactor |
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+ | Mixed Precision | fp16 |
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+ | Gradient Accumulation | 4 steps |
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+ | Max Length | 512 tokens |
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+
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+ ## Evaluation Results
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+ | Metric | Value |
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+ |--------|-------|
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+ | ROUGE-1 | 0.174 |
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+ | ROUGE-2 | 0.045 |
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+ | ROUGE-L | 0.135 |
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+
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+ ## Basic Inference
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+
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+ ```python
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+ from transformers import pipeline
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+ summarizer = pipeline(
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+ "text2text-generation",
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+ model="your_hf_username/your_model_name"
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+ )
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+ dialogue_example = """
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+ A: The router keeps disconnecting every hour.
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+ B: Have you tried firmware update?
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+ A: Not yet, how do I do that?
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+ B: Download latest version from our support site.
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+ """
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+ summary = summarizer(
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+ f"Summarize this dialogue:\n{dialogue_example}\nSummary:",
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+ max_length=150,
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+ num_beams=3
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+ )['generated_text']
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+ print(summary)
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+ ```
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+
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+ ## Training Procedure
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+ - **Hardware**: T4 GPU on Kaggle
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+ - **Framework**: PyTorch with Hugging Face Transformers
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+ - **Training Time**: ~45 minutes (Kaggle free tier)
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+
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+ ## Recommendations
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+ - Use beam search (num_beams=3-5) for better results
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+ - Combine with post-processing for formatting
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+ - Fine-tune longer for complex dialogues
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+
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+ ## Limitations
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+ - Struggles with multi-topic dialogues
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+ - May miss subtle contextual cues
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+ - Best performance on short conversations (<500 tokens)
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+
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+ ## License
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+ Apache 2.0 (Same as base FLAN-T5 model)
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+
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+ ## Citation
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+ @misc{dialogsum2021,
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+ title={DialogSum: A Real-Life Scenario Dialogue Summarization Dataset},
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+ author={Karthick Krishnamurthy},
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+ year={2021},
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+ howpublished={HuggingFace Datasets},
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+ }