This is mistralai/Mistral-7B-v0.1, but with the special tokens added for ChatML, and then lightly finetuned with sft using a ChatML formatted dataset: andysalerno/ansalern-nectar-inputoutput
The training was very light, so while this model correctly follows ChatML formatting, it is not intended to be a chat model.
Rather, it is intended to be a base for further fine-tuning models that will use ChatML.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 60.93 |
| AI2 Reasoning Challenge (25-Shot) | 61.35 |
| HellaSwag (10-Shot) | 82.23 |
| MMLU (5-Shot) | 63.40 |
| TruthfulQA (0-shot) | 48.49 |
| Winogrande (5-shot) | 77.66 |
| GSM8k (5-shot) | 32.45 |
- Downloads last month
- 293
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for andysalerno/mistral-sft-v3
Dataset used to train andysalerno/mistral-sft-v3
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard61.350
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard82.230
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.400
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard48.490
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.660
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard32.450