This is OpenLLaMA 3B V2 finetuned on Puffin for 1 epochs.
Prompt template:
### HUMAN:
{prompt}
### RESPONSE:
<leave a newline for the model to answer>
GGML quants available here.
GPTQ quants available here.
Note: Don't expect this model to be good, I was just starting out to finetune. So don't roast me please!
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 41.13 |
| ARC (25-shot) | 41.81 |
| HellaSwag (10-shot) | 72.3 |
| MMLU (5-shot) | 26.36 |
| TruthfulQA (0-shot) | 38.33 |
| Winogrande (5-shot) | 67.01 |
| GSM8K (5-shot) | 0.99 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 41.13 |
| AI2 Reasoning Challenge (25-Shot) | 41.81 |
| HellaSwag (10-Shot) | 72.30 |
| MMLU (5-Shot) | 26.36 |
| TruthfulQA (0-shot) | 38.33 |
| Winogrande (5-shot) | 67.01 |
| GSM8k (5-shot) | 0.99 |
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Dataset used to train acrastt/Griffin-3B
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard41.810
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard72.300
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard26.360
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard38.330
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard67.010
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard0.990