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--- |
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library_name: peft |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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datasets: |
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- argilla/ultrafeedback-binarized-preferences-cleaned |
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- >- |
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flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl |
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language: |
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- en |
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--- |
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# Model Card for Phi-3-mini-4k-instruct DPO |
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## Model Details |
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- **Model Name:** Phi-3-mini-4k-instruct DPO |
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- **Publisher:** Team chatterbox, EPFL |
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- **Model Type:** Language Model, Fine-tuned with direct preference optimization (DPO) |
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- **Training Environment:** Trained on the EPFL SCITAS cluster using a 32GB GPU. |
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## Intended Use |
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- **Primary Applications:** This model is designed as part of an AI-Tutor system. |
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- **Intended Audience:** Educators, students, and developers creating educational AI applications. |
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## Model/Data Description |
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### Training Data |
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- **Datasets Used:** |
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- **Milestone 1 Dataset:** Includes 1522 unique questions with preference pairs based on the 'overall' rating, totaling 20k+ usable entries after processing. |
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- **Stack Exchange Dataset:** Filters content from specific domains within the Stack Exchange network, using upvoted and downvoted answers to form preference pairs. Total entries after preprocessing: 54458. |
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- **Ultra Feedback:** Utilizes responses rated on criteria like truthfulness and helpfulness to form preference pairs, with a total of 60917 entries after preprocessing. |
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- **Preprocessing Details:** Entries with identical chosen and rejected answers were removed. Datasets were formatted as JSONL where each line represents a JSON object with a "prompt", "chosen", and "rejected" response. |
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## Training Procedure |
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- **Configurations:** (Refer to the provided `training_args` and `trainer` configuration) |
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- **Evaluation Metrics:** The primary metric for model performance is `eval_loss`, with the aim to minimize this value. |
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## Evaluation Results |
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- **Accuracies:** eval/rewards/accuracies - 0.83 |
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- **Loss:** eval/loss - 0.47 |
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- **Margins:** eval/margins - 4.31 |
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### MT-Bench |
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- **Single Grading Score, Overall Avg.** - 8.2 |
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- **STEM Score** - 9.8 (higher than GPT-4) |
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%3C!-- HTML_TAG_END --> |
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## References |
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- **[Include references and citations for datasets, tools, and methodologies used.]** |
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- PEFT 0.11.1 |
