Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
wandb_-_gemma-2b-zephyr-sft-8bits – AI Model by RichardErkhov | AlphaNeural AI
You can deploy this model and start earning money today!
RichardErkhov
/
wandb_-_gemma-2b-zephyr-sft-8bits
like
0
safetensors
gemma
8-bit
bitsandbytes
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
Quantization made by Richard Erkhov.
Github
Discord
Request more models
gemma-2b-zephyr-sft - bnb 8bits
Model creator:
https://huggingface.co/wandb/
Original model:
https://huggingface.co/wandb/gemma-2b-zephyr-sft/
Original model description:
license: other library_name: transformers datasets:
HuggingFaceH4/ultrachat_200k base_model: google/gemma-2b license_name: gemma-terms-of-use license_link:
https://ai.google.dev/gemma/terms
model-index:
name: gemma-2b-zephyr-sft results:
task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
type: acc_norm value: 49.74 name: normalized accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
type: acc_norm value: 72.38 name: normalized accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
type: acc value: 41.37 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
type: mc2 value: 34.42 source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
type: acc value: 66.93 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
type: acc value: 18.27 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=wandb/gemma-2b-zephyr-sft
name: Open LLM Leaderboard
Visualize in Weights & Biases
Gemma 2B Zephyr SFT
The
Zephyr
SFT recipe applied on top of Gemma 2B
Model description
Model type:
A 2.5B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
Language(s) (NLP):
Primarily English
Finetuned from model:
google/gemma-7b
Recipe
We trained using the
alignment handbook recipe
and logging to W&B
Visit the
W&B workspace here
License
This model has the same license as the
original Gemma model collection
Compute provided by Lambda Labs - 8xA100 80GB node
Around 2 hours to train
Open LLM Leaderboard Evaluation Results
Detailed results can be found
here
Metric
Value
Avg.
47.18
AI2 Reasoning Challenge (25-Shot)
49.74
HellaSwag (10-Shot)
72.38
MMLU (5-Shot)
41.37
TruthfulQA (0-shot)
34.42
Winogrande (5-shot)
66.93
GSM8k (5-shot)
18.27