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-2t | 0.2807 | 0.5463 | 0.7067 | 0.5683 |
palmer-001 | 0.2807 | 0.5524 | 0.7106 | 0.5896 |
tinyllama-2.5t | 0.3191 | 0.5896 | 0.7307 | 0.5872 |
palmer-002 | 0.3242 | 0.5956 | 0.7345 | 0.5888 |
palmer-002-ultra | 0.3319 | 0.5877 | 0.7252 | 0.6038 |
This is a continuation on palmer-x-002
. As of now, this is the best overall model.
training
Training took ~7.5 P100 gpu hours. It was trained on 50,000 gpt-4 shuffled samples. palmer was fine-tuned using lower learning rates ensuring it keeps as much general knowledge as possible.
prompt
no prompt
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