Antares-11b-v2 / README.md
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---
license: cc-by-nc-4.0
datasets:
- jondurbin/bagel-v0.3
base_model: decapod-research/Antares-11b-v1
model-index:
- name: Antares-11b-v2
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: 69.03
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
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: 87.54
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
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: 66.19
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
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: 59.17
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
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: 83.19
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
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: 60.5
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=decapoda-research/Antares-11b-v2
name: Open LLM Leaderboard
---
Fine-tune of Upstage AI's SOLAR-10.7B-Instruct-v1.0 model, using the OpenHermes, Platypus, and Capybara datasets. Additionally fine-tuned on Jon Durbin's Bagel v0.3, plus a few unreleased datasets.
Fine-tuned on 8x4090s for 1.25 epochs.
### Model Sources [optional]
- **Repository:** TBD
- **Demo:** TBD
## Bias, Risks, and Limitations
This fine-tune has had zero alignment, safety data, or anything else shoved down it's throat.
## Training Details
### Training Data
See the sidebar for links to the relevant datasets.
### Training Procedure
Trained using QLORA via the Axolotl tool.
## Evaluation
TBD
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.6.0
# [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_decapoda-research__Antares-11b-v2)
| Metric |Value|
|---------------------------------|----:|
|Avg. |70.94|
|AI2 Reasoning Challenge (25-Shot)|69.03|
|HellaSwag (10-Shot) |87.54|
|MMLU (5-Shot) |66.19|
|TruthfulQA (0-shot) |59.17|
|Winogrande (5-shot) |83.19|
|GSM8k (5-shot) |60.50|