license: other
license_name: yi-license
license_link: LICENSE
model-index:
- name: Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 65.96
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 83.89
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 74.76
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 57.08
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 78.69
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
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: 55.5
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=adamo1139/Yi-34B-200K-AEZAKMI-RAW-2301-LoRA
name: Open LLM Leaderboard
THIS MODEL IS EXPERIMENTAL AND MIGHT BE BUGGY, I DIDN'T PERFECT THE STRENGTH OF DPO AND SFT YET.
Submitting to Open LLM leaderboard with base model yi-34b-200k-llamafied to see whether there's a point in merging a lora over a lora if both have the same lora_r or if it doesn't matter.
Another AEZAKMI v2 finetune over Yi-34B-200K-rawrr-r3. Sequence length 2200 I was able to squeeze that in using Unsloth, script I used is in this repo. Training took around 18 hours on local RTX 3090 Ti. Will be uploading fp16 and exl2 soon. So far it seems like de-contaminating Yi worked nicely. This lora goes over Yi-34B-200K-rawrr1-LORA-DPO-experimental-r3 lora. So first get Yi-34B-200K llamafied, merge in Yi-34B-200K-rawrr1-LORA-DPO-experimental-r3, then merge in this lora.
Credits for mlabonne (I was using his Mistral fine-tuning script pieces for dataset preparation), Daniel Han and Michael Han (Unsloth AI team)
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 69.31 |
| AI2 Reasoning Challenge (25-Shot) | 65.96 |
| HellaSwag (10-Shot) | 83.89 |
| MMLU (5-Shot) | 74.76 |
| TruthfulQA (0-shot) | 57.08 |
| Winogrande (5-shot) | 78.69 |
| GSM8k (5-shot) | 55.50 |