metadata
datasets:
- mindchain/wikitext2
- yahma/alpaca-cleaned
metrics:
- perplexity
- accuracy
base_model:
- TinyLlama/TinyLlama_v1.1
model-index:
- name: TinyLlama_v1.1_mix_wikitext_alpaca_2bit_BitDistiller_baseline
results:
- task:
type: multiple-choice
name: QA Benchmarking
dataset:
type: allenai/arc
name: ARC-Challenge
config: challenge
split: test
metrics:
- type: accuracy
name: Accuracy
value: 0.2150170648464164
- type: accuracy
name: Normalized Accuracy
value: 0.24573378839590443
- task:
type: multiple-choice
name: QA Benchmarking
dataset:
type: hellaswag
name: HellaSwag
split: test
metrics:
- type: accuracy
name: Accuracy
value: 0.3240390360485959
- type: accuracy
name: Normalized Accuracy
value: 0.37333200557657836
- task:
type: multiple-choice
name: QA Benchmarking
dataset:
type: piqa
name: PIQA
split: validation
metrics:
- type: accuracy
name: Accuracy
value: 0.6082698585418934
- type: accuracy
name: Normalized Accuracy
value: 0.6071817192600653
- task:
type: multiple-choice
name: QA Benchmarking
dataset:
type: winogrande
name: Winogrande
split: test
metrics:
- type: accuracy
name: Accuracy
value: 0.5201262825572218
- task:
type: multiple-choice
name: QA Benchmarking
dataset:
type: aggregated
name: QA-Avg
metrics:
- type: accuracy
name: QA Average
value: 0.4168630604985319
- task:
type: language-modeling
name: Language Modeling
dataset:
type: wikitext
name: WikiText-2
split: test
metrics:
- type: perplexity
name: Perplexity
value: 22.655162811279297
TODO: check the splits of each dataset
Loss curves:
