Medical Merges
Collection
Playful merges that try to improve small medical LMs by merging them with models with higher reasoning capabilities.
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35 items
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Updated
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3
Technoculture/MedMerge-6-7b-alpha-dpo
Open LLM Leaderboard
| Model Name | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---|---|---|---|---|---|---|
| Orca-2-7b | 78.4 | 76.1 | 53.7 | 52.4 | 74.2 | 47.2 |
| LLAMA-2-7b | 43.2 | 77.1 | 44.4 | 38.7 | 69.5 | 16 |
| MT7Bi-sft | 54.1 | 75.11 | - | 43.08 | 72.14 | 15.54 |
| MedMerge-6-7b | 29.52 | 41.04 | - | 37.53 | 59.35 | 0.91 |
| MedMerge-6-7b-alpha-dpo | 54.27 | 75.6 | 52.65 | 43.94 | 71.03 | 26.16 |
Training Details
- GPU: Nvidia A100 Tensor Core GPU
- Total Batches: 4266
- Epochs: 3
- Duration: 3 hours, 57 minutes, and 00 seconds
DPO Training Dataset Mixture
| Dataset Name | Original Size(Rows) | Ratio | Size After Ratio(Rows) |
|---|---|---|---|
| argilla/distilabel-math-preference-dpo | 2.4k | 1.0 | 2.4k |
| argilla/distilabel-intel-orca-dpo-pairs | 12.9k | 0.5 | 6.45k |
| jondurbin/truthy-dpo-v0.1 | 1.04k | 1.0 | 1.04k |
| argilla/distilabel-capybara-dpo-7k-binarized | 7.5k | 0.2 | 1.5k |
| Total Size: 11.38k |
Training Loss Plot
Training Loss Smoothed Plot
For full details of this dpo-training please read our notebook.
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Model tree for Technoculture/MedMerge-6-7b-alpha-dpo
Base model
Technoculture/MT7Bi-sft