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Adding Evaluation Results
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---
language:
- en
tags:
- llama
datasets:
- chargoddard/Open-Platypus-Chat
model-index:
- name: platypus2-22b-relora
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: 57.51
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
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: 82.36
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
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: 54.94
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
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: 43.62
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
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: 77.11
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
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: 6.29
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/platypus2-22b-relora
name: Open LLM Leaderboard
---
Experimental ReLoRA-trained model using the OpenPlatypus dataset. Ran for one epoch, with three lora restarts.
Not recommended for use yet. Mostly tossing this up for testing.
Base model was [llama2-22b-blocktriangular](https://huggingface.co/chargoddard/llama2-22b-blocktriangular).
Relevant training parameters:
```
adapter: qlora
load_in_4bit: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.001
lora_target_linear: true
relora_steps: 150
relora_warmup_steps: 10
gradient_accumulation_steps: 2
micro_batch_size: 3
```
Uses the same prompt format as [Ypotryll-22b](https://huggingface.co/chargoddard/ypotryll-22b-epoch2-qlora).
Prefix messages with `" ***System:"`, `" ***Query:"`, or `" ***Response:"`, paying attention to whitespace.
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# [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_chargoddard__platypus-2-22b-relora)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 52.21 |
| ARC (25-shot) | 57.68 |
| HellaSwag (10-shot) | 82.44 |
| MMLU (5-shot) | 55.33 |
| TruthfulQA (0-shot) | 43.61 |
| Winogrande (5-shot) | 77.35 |
| GSM8K (5-shot) | 6.6 |
| DROP (3-shot) | 42.46 |
# [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_chargoddard__platypus2-22b-relora)
| Metric |Value|
|---------------------------------|----:|
|Avg. |53.64|
|AI2 Reasoning Challenge (25-Shot)|57.51|
|HellaSwag (10-Shot) |82.36|
|MMLU (5-Shot) |54.94|
|TruthfulQA (0-shot) |43.62|
|Winogrande (5-shot) |77.11|
|GSM8k (5-shot) | 6.29|