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---
license: apache-2.0
language:
- en
datasets:
- appvoid/no-prompt-15k
pipeline_tag: text-generation
---
# no-prompt
### a sheared-llama-1.3b fine-tuning
This model uses an 1.3 billion parameters model as base to be further fine-tuned on the same data as palmer. It works pretty good and even surpasses sota model on `hellaswag`.
### evaluation
|Model| ARC_C| HellaSwag| PIQA| Winogrande|
|------|-----|-----------|------|-------------|
|tinyllama-2t| 0.2807| 0.5463| 0.7067| 0.5683|
|palmer-001 | 0.2807| 0.5524| 0.7106| 0.5896|
|sheared-1.3b| 0.2910| 0.5935| 0.7339| 0.5809|
|no-prompt-1.3b| 0.3157| **0.6022**| 0.7334| 0.5864|
|falcon-rw-1b-instruct-openorca (sota) | **0.3362**| 0.5997| **0.7394**| **0.6148**|
This model was trained on less than 25% of the dataset yet achieves competitive performance to current sota on open llm leaderboard.
### training
Training took ~5 P100 gpu hours. It was trained on 15,000 gpt-4 shuffled samples. palmer was fine-tuned using lower learning rates ensuring it keeps as much general knowledge as possible.
### prompt
```
no prompt
```
### limitations
Hallucinations are frequent, just as any transformer model this size.
<a href="https://ko-fi.com/appvoid" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 48px !important;width: 180px !important; filter: invert(70%);" ></a> |