license, widget, model-index
license
widget
model-index
mit
text
<|system|>
You are a helpful assistant</s>
<|user|>
Can you explain to me how quantum computing works?</s>
<|assistant|>
name
results
Tinyllama-Cinder-1.3B-Reason-Test
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
34.56
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
58.24
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
25.79
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
63.93
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
4.85
accuracy
1.3B test of two Cinder models merged layers 1-22 and 18-22, trained on math and step by step reasoning. Model Overview Cinder is an AI chatbot tailored for engaging users in scientific and educational conversations, offering companionship, and sparking imaginative exploration. It is built on the TinyLlama 1.1B parameter model and trained on a unique combination of datasets. Testing on Reason-with-cinder dataset.
Detailed results can be found here
Metric
Value
Avg.
37.88
AI2 Reasoning Challenge (25-Shot)
34.56
HellaSwag (10-Shot)
58.24
MMLU (5-Shot)
25.79
TruthfulQA (0-shot)
39.93
Winogrande (5-shot)
63.93
GSM8k (5-shot)
4.85