File size: 4,273 Bytes
631eb94 26a92bd 631eb94 ee716b9 26a92bd 631eb94 ee716b9 26a92bd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 |
---
language:
- en
license: mit
library_name: transformers
tags:
- peft
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 60.92
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 83.23
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 60.78
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 53.33
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 77.19
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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: 43.21
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
name: Open LLM Leaderboard
---
LoRA adapter for kaitchup/Maixtchup-4x7b briefly fine-tuned on UltraChat.
To load and use this adapter:
```
model_name = "kaitchup/Maixtchup-4x7b"
#Tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
compute_dtype = getattr(torch, "float16")
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=compute_dtype,
bnb_4bit_use_double_quant=True,
)
model = AutoModelForCausalLM.from_pretrained(
model_name, quantization_config=bnb_config, device_map="auto", attn_implementation="flash_attention_2",
)
model.config.use_cache = True
model = PeftModel.from_pretrained(model, "kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat")
```
# [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_kaitchup__Maixtchup-4x7b-QLoRA-SFT-UltraChat)
| Metric |Value|
|---------------------------------|----:|
|Avg. |63.11|
|AI2 Reasoning Challenge (25-Shot)|60.92|
|HellaSwag (10-Shot) |83.23|
|MMLU (5-Shot) |60.78|
|TruthfulQA (0-shot) |53.33|
|Winogrande (5-shot) |77.19|
|GSM8k (5-shot) |43.21|
|