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Sentiment Analysis On Sst 2 Binary

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Paper Title
T5-11B97.5Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
MT-DNN-SMART97.5SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
T5-3B97.4Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
MUPPET Roberta Large97.4Muppet: Massive Multi-task Representations with Pre-Finetuning
StructBERTRoBERTa ensemble97.1StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
ALBERT97.1ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
XLNet (single model)97XLNet: Generalized Autoregressive Pretraining for Language Understanding
ELECTRA96.9ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
RoBERTa-large 355M + Entailment as Few-shot Learner96.9Entailment as Few-Shot Learner
XLNet-Large (ensemble)96.8XLNet: Generalized Autoregressive Pretraining for Language Understanding
FLOATER-large96.7Learning to Encode Position for Transformer with Continuous Dynamical Model
MUPPET Roberta base96.7Muppet: Massive Multi-task Representations with Pre-Finetuning
RoBERTa (ensemble)96.7RoBERTa: A Robustly Optimized BERT Pretraining Approach
DeBERTa (large)96.5DeBERTa: Decoding-enhanced BERT with Disentangled Attention
MT-DNN-ensemble96.5Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding
RoBERTa-large 355M (MLP quantized vector-wise, fine-tuned)96.4LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
ASA + RoBERTa96.3Adversarial Self-Attention for Language Understanding
T5-Large 770M96.3Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Snorkel MeTaL(ensemble)96.2Training Complex Models with Multi-Task Weak Supervision
PSQ (Chen et al., 2020)96.2A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
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