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---
language:
- en
license: other
tags:
- code
datasets:
- reciprocate/dpo_ultra-capybara-code_filtered-best
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen1.5-7B-Chat/blob/main/LICENSE
pipeline_tag: text-generation
model-index:
- name: Coder1.8-ORPO-TEST
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: 38.82
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
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: 60.48
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
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: 46.7
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
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: 41.38
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
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: 59.75
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
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: 27.45
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=raincandy-u/Coder1.8-ORPO-TEST
name: Open LLM Leaderboard
---
# Coder1.8-ORPO-TEST
## Model Description
Test model for ORPO finetune method, trained on ~20k code examples for 1 epoch on 2 x A40 cards with 4-bit QLora (lora rank=lora alpha=16).
## Disclaimer
This is a test model and may generate incorrect responses. Use at your own risk.
## Train Details
- Base: Qwen1.5-1.8B
- Training Data: ~20k [code examples](https://huggingface.co/datasets/reciprocate/dpo_ultra-capybara-code_filtered-best)
- Epochs: 1
- Method: ORPO
- Hardware: 2 x A40
- Quantization: 4-bit QLora
- Lora Rank/Alpha: 16
# Limitations
Limited training data and quantization may impact performance.
# Join the Discussion
Have questions or feedback? Join our Discord server [Here](https://discord.gg/KugcbJX5).
# [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_raincandy-u__Coder1.8-ORPO-TEST)
| Metric |Value|
|---------------------------------|----:|
|Avg. |45.76|
|AI2 Reasoning Challenge (25-Shot)|38.82|
|HellaSwag (10-Shot) |60.48|
|MMLU (5-Shot) |46.70|
|TruthfulQA (0-shot) |41.38|
|Winogrande (5-shot) |59.75|
|GSM8k (5-shot) |27.45|
|