Puma-3B / README.md
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Adding Evaluation Results (#8)
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---
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- totally-not-an-llm/sharegpt-hyperfiltered-3k
pipeline_tag: text-generation
model-index:
- name: Puma-3B
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: 41.3
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
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: 71.85
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
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: 27.51
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
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: 38.34
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
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: 66.38
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
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: 0.76
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B
name: Open LLM Leaderboard
---
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This is [OpenLLaMA 3B V2](https://huggingface.co/openlm-research/open_llama_3b_v2) finetuned on [ShareGPT Hyperfiltered](https://huggingface.co/datasets/totally-not-an-llm/sharegpt-hyperfiltered-3k) for 1 epochs.
Prompt template:
```
### HUMAN:
{prompt}
### RESPONSE:
<leave a newline for the model to answer>
```
GGML quants available [here](https://huggingface.co/TheBloke/Puma-3b-GGML).</br>
GPTQ quants available [here](https://huggingface.co/TheBloke/Puma-3b-GPTQ).
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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_acrastt__Puma-3B)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 41.02 |
| ARC (25-shot) | 41.3 |
| HellaSwag (10-shot) | 71.85 |
| MMLU (5-shot) | 27.51 |
| TruthfulQA (0-shot) | 38.34 |
| Winogrande (5-shot) | 66.38 |
| GSM8K (5-shot) | 0.76 |
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_acrastt__Puma-3B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |41.02|
|AI2 Reasoning Challenge (25-Shot)|41.30|
|HellaSwag (10-Shot) |71.85|
|MMLU (5-Shot) |27.51|
|TruthfulQA (0-shot) |38.34|
|Winogrande (5-shot) |66.38|
|GSM8k (5-shot) | 0.76|