language, license, tags, pipeline_tag, model-index
| language |
license |
tags |
pipeline_tag |
model-index |
|
|
mit |
|
text-generation |
| name |
results |
| FusionNet_linear |
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
config |
split |
args |
| AI2 Reasoning Challenge (25-Shot) |
ai2_arc |
ARC-Challenge |
test |
|
|
| type |
value |
name |
| acc_norm |
71.25 |
normalized accuracy |
|
|
|
|
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
split |
args |
| HellaSwag (10-Shot) |
hellaswag |
validation |
|
|
| type |
value |
name |
| acc_norm |
88.44 |
normalized accuracy |
|
|
|
|
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
config |
split |
args |
| MMLU (5-Shot) |
cais/mmlu |
all |
test |
|
|
| type |
value |
name |
| acc |
66.35 |
accuracy |
|
|
|
|
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
config |
split |
args |
| TruthfulQA (0-shot) |
truthful_qa |
multiple_choice |
validation |
|
|
|
|
|
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
config |
split |
args |
| Winogrande (5-shot) |
winogrande |
winogrande_xl |
validation |
|
|
| type |
value |
name |
| acc |
83.27 |
accuracy |
|
|
|
|
| task |
dataset |
metrics |
source |
| type |
name |
| text-generation |
Text Generation |
|
| name |
type |
config |
split |
args |
| GSM8k (5-shot) |
gsm8k |
main |
test |
|
|
| type |
value |
name |
| acc |
65.35 |
accuracy |
|
|
|
|
|
|
|
FusionNet_linear
Fine-tuned model on English language using linear Fusion method.
Model description
This is an experiment with the linear Fusion method of FusionNet. This model has 10.7B parameters, and this model is fine-tuned. Enjoy!
Detailed results can be found here
| Metric |
Value |
| Avg. |
74.43 |
| AI2 Reasoning Challenge (25-Shot) |
71.25 |
| HellaSwag (10-Shot) |
88.44 |
| MMLU (5-Shot) |
66.35 |
| TruthfulQA (0-shot) |
71.94 |
| Winogrande (5-shot) |
83.27 |
| GSM8k (5-shot) |
65.35 |