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uukuguy/Mistral-7B-OpenOrca-lora-merged
Mistral-7B-OpenOrca-lora-merged is a text generation model from uukuguy. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as llama2.
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Updated Oct 18, 2023
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From the Hugging Face model README
This is a test.
This is a regenerated model that combines the base model Mistral-7B-v0.1 with the LoRA model Mistral-7B-OpenOrca-lora.
This LoRA model is extracted from the efficient parameter fine-tuned model (Mistral-7B-OpenOra), and now it needs to be verified whether this LoRA model can achieve comparable performance with the original model.
The final goal is to create a toolkit that can simultaneously load multiple LoRA modules, and automatically switch to the appropriate combination of LoRA modules based on user queries to generate the best answer.
The source code is here
Extract lora model Mistral-7B-OpenOrca-lora from Mistral-7B-OpenOrca;
Merge the base model Mistral-7B-v0.1 with lora model to Mistral-7B-OpenOrca-lora-merged
LLM Evaluation ...
| ARC_acc_norm (25-shot) | HellaSwag_acc_norm (10-shot) | MMLU_acc (5-shot) | TruthfulQA_mc2 (0-shot) | GSM8K_acc (8-shot) | Open LLM Score | |
|---|---|---|---|---|---|---|
| Mistral-7B-OpenOrca | 71 | 83 | 61.42 | 45 | 40 | 65.11 |
| r=256 | 68 | 84 | 64.28 | 46.953 | 41 | 65.81 |
| r=64 | 67 | 84 | 64.26 | 47.32 | 41 | 65.65 |
| r=16 | 65 | 83 | 62.84 | 46.95 | 38 | 64.45 |
| ARC_acc_norm (25-shot) | HellaSwag_acc_norm (10-shot) | MMLU_acc (5-shot) | TruthfulQA_mc2 (0-shot) | Open LLM Score | |
|---|---|---|---|---|---|
| Mistral-7B-SlimOrca | 62.54 | 83.86 | 62.77 | 54.23 | 65.85 |
| Mistral-7B-OpenOrca | 64.08 | 83.99 | 62.24 | 53.05 | 65.84 |
| Metric | Mistral-7B-OpenOrca | Mistral-7B-OpenOrca-lora | Mistral-7B-OpenOrca-lora-merged |
|---|---|---|---|
| ARC | 64.08 | ||
| HellaSwag | 83.99 | ||
| MMLU | 62.24 | ||
| TruthfulQA | 53.05 | ||
| Average | 65.84 |
| Metric | Mistral-7B-OpenOrca | Mistral-7B-OpenOrca-lora | Mistral-7B-OpenOrca-lora-merged |
|---|---|---|---|
| humaneval-python | 35.976 |
The following bitsandbytes quantization config was used during training: