Language Modelling On Lambada

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Accuracy	Paper Title	Repository
OPT-175B (50% Sparsity)	0.02	SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot	-
GLM-XXLarge (bidirectional)	72.35	GLM: General Language Model Pretraining with Autoregressive Blank Infilling	-
GPT-3 175B (Few-Shot)	86.4	Language Models are Few-Shot Learners	-
test	0.01	Test-Time Training with Self-Supervision for Generalization under Distribution Shifts	-
Megatron-Turing NLG 530B (Few-Shot)	Megatron-Turing NLG 530B (Few-Shot)	Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model	-
PaLM 2-M (one-shot)	83.7	PaLM 2 Technical Report	-
GPT-3 13B (Zero-Shot)	72.5	Language Models are Few-Shot Learners	-
Gated-Attention Reader (+ features)	49.0	Broad Context Language Modeling as Reading Comprehension	-
GPT-2 1.5B (Zero Shot)	63.24	Language Models are Unsupervised Multitask Learners	-
GPT-3 2.7B (Zero-Shot)	67.1	Language Models are Few-Shot Learners	-
Pythia 12B(Zero-Shot)	-	Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling	-
PaLM 2-L (one-shot)	86.9	PaLM 2 Technical Report	-
LLaMA-30B+CFG (zero-shot)	83.9	Stay on topic with Classifier-Free Guidance	-
Universal Transformer (w/ dynamic halting)	56.25	Universal Transformers	-
SparseGPT (175B, 2:4 Sparsity)	79.47	SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot	-
SparseGPT (175B, 50% Sparsity)	76.51	SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot	-
PaLM-540B (Zero-Shot)	77.9	PaLM: Scaling Language Modeling with Pathways	-
Pythia 6.9B (0-shot)	67.28	Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling	-
GLaM 62B/64E (One-Shot)	80.9	GLaM: Efficient Scaling of Language Models with Mixture-of-Experts	-
Residual Shuffle-Exchange network	54.34	Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences	-

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