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---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
datasets:
- appvoid/no-prompt-15k
---
# palmer
### a better base model
palmer is a series of ~1b parameters language models fine-tuned to be used as base models instead of using custom prompts for tasks. This means that it can be further fine-tuned on more data with custom prompts as usual or be used for downstream tasks as any base model you can get. The model has the best of both worlds: some "bias" to act as an assistant, but also the abillity to predict the next-word from its internet knowledge base. It's a 1.1b llama 2 model so you can use it with your favorite tools/frameworks.
### evaluation
|Model| ARC_C| HellaSwag| PIQA| Winogrande|
|------|-----|-----------|------|-------------|
|tinyllama-2 | 0.2807 |0.5463| 0.7067 | 0.5683|
|palmer-001 | 0.2807 |0.5524| 0.7106 | 0.5896|
|tinyllama-2.5| 0.3191 |0.5896| 0.7307 | 0.5872|
|tinyllama-3 | 0.3029 |0.5935| 0.7329 | **0.5959**|
|palmer-002|**0.3242**|**0.5956**|**0.7345**| 0.5888|
This model shows exceptional performance and as of now is the best tinyllama-size base model. Furthermore, this proves LIMA paper point and serves as a good open-source alternative to openai's `babbage-002`.
### training
Training took ~3.5 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
```
<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> |