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The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Model Card for Model ID
microsoft/Phi-3-medium-4k-instruct trained with ORPO trainer.
Training Details
Training Data
mlabonne/orpo-dpo-mix-40k is used for finetuning this model.
[More Information Needed]
Training Procedure
Trained with ORPO trainer, and only first 5K rows are used for finetuning (5K out of 40K).
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 26.84 |
| IFEval (0-Shot) | 40.22 |
| BBH (3-Shot) | 46.63 |
| MATH Lvl 5 (4-Shot) | 16.69 |
| GPQA (0-shot) | 7.38 |
| MuSR (0-shot) | 10.53 |
| MMLU-PRO (5-shot) | 39.60 |
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Model tree for BlackBeenie/Neos-Phi-3-14B-v0.1
Dataset used to train BlackBeenie/Neos-Phi-3-14B-v0.1
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard40.220
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard46.630
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard16.690
- acc_norm on GPQA (0-shot)Open LLM Leaderboard7.380
- acc_norm on MuSR (0-shot)Open LLM Leaderboard10.530
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard39.600