prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the Vector-wise model in the LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT-IML 175B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the FLAN 137B zero-shot model in the Finetuned Language Models Are Zero-Shot Learners paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT-IML 30B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the ELECTRA model in the paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the PaLM 2-M (one-shot) model in the PaLM 2 Technical Report paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the ERNIE 2.0 Large model in the ERNIE 2.0: A Continual Pre-training Framework for Language Understanding paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the T5-Base model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the MLM+ del-span model in the CLEAR: Contrastive Learning for Sentence Representation paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the PaLM 2-L (one-shot) model in the PaLM 2 Technical Report paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the SpanBERT model in the SpanBERT: Improving Pre-training by Representing and Predicting Spans paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the PaLM 2-S (one-shot) model in the PaLM 2 Technical Report paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the BigBird model in the Big Bird: Transformers for Longer Sequences paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the ERNIE 2.0 Base model in the ERNIE 2.0: A Continual Pre-training Framework for Language Understanding paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the Neo-6B (QA + WS) model in the Ask Me Anything: A simple strategy for prompting language models paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the RealFormer model in the RealFormer: Transformer Likes Residual Attention paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the SqueezeBERT model in the SqueezeBERT: What can computer vision teach NLP about efficient neural networks? paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the SMART model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the BERT-LARGE model in the BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the T5-Small model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the data2vec model in the data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the Bloomberg GPT (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the GPT-3 175B (Few-Shot) model in the Language Models are Few-Shot Learners paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the FNet-Large model in the FNet: Mixing Tokens with Fourier Transforms paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the ERNIE model in the ERNIE: Enhanced Language Representation with Informative Entities paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the AlexaTM 20B model in the AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT-IML 1.3B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the DistilBERT model in the DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the TinyBERT model in the TinyBERT: Distilling BERT for Natural Language Understanding paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the Neo-6B (QA) model in the Ask Me Anything: A simple strategy for prompting language models paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT 175B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the N-Grammer model in the N-Grammer: Augmenting Transformers with latent n-grams paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the Neo-6B (few-shot) model in the Ask Me Anything: A simple strategy for prompting language models paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT 30B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the 24hBERT model in the How to Train BERT with an Academic Budget paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the BLOOM 176B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT 66B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the OPT 1.3B model in the OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the GPT-NeoX (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the SMARTRoBERTa model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the SMART-BERT model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the RTE dataset? | Accuracy, Dev Accuracy |
What metrics were used to measure the aESIM model in the Attention Boosted Sequential Inference Model paper on the Quora Question Pairs dataset? | Accuracy |
What metrics were used to measure the T5-11B model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the T5 model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the T5-3B model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ALBERT model in the ALBERT: A Lite BERT for Self-supervised Learning of Language Representations paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the DeBERTa (large) model in the DeBERTa: Decoding-enhanced BERT with Disentangled Attention paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Adv-RoBERTa ensemble model in the StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the RoBERTa model in the RoBERTa: A Robustly Optimized BERT Pretraining Approach paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the XLNet (single model) model in the XLNet: Generalized Autoregressive Pretraining for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Vector-wise model in the LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the T5-Large model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ERNIE 2.0 Large model in the ERNIE 2.0: A Continual Pre-training Framework for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SpanBERT model in the SpanBERT: Improving Pre-training by Representing and Predicting Spans paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the BERT-Large model in the FNet: Mixing Tokens with Fourier Transforms paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ASA + RoBERTa model in the Adversarial Self-Attention for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the MT-DNN-ensemble model in the Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Snorkel MeTaL (ensemble) model in the Training Complex Models with Multi-Task Weak Supervision paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the BigBird model in the Big Bird: Transformers for Longer Sequences paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the T5-Base model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the MT-DNN model in the Multi-Task Deep Neural Networks for Natural Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the BERT-LARGE model in the BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the RealFormer model in the RealFormer: Transformer Likes Residual Attention paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the gMLP-large model in the Pay Attention to MLPs paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ERNIE 2.0 Base model in the ERNIE 2.0: A Continual Pre-training Framework for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ASA + BERT-base model in the Adversarial Self-Attention for Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the 24hBERT model in the How to Train BERT with an Academic Budget paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the ERNIE model in the ERNIE: Enhanced Language Representation with Informative Entities paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Charformer-Tall model in the Charformer: Fast Character Transformers via Gradient-based Subword Tokenization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the TinyBERT model in the TinyBERT: Distilling BERT for Natural Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the T5-Small model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the MFAE model in the What Do Questions Exactly Ask? MFAE: Duplicate Question Identification with Multi-Fusion Asking Emphasis paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Finetuned Transformer LM model in the paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Finetuned Transformer LM model in the Improving Language Understanding by Generative Pre-Training paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SqueezeBERT model in the SqueezeBERT: What can computer vision teach NLP about efficient neural networks? paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the FNet-Large model in the FNet: Mixing Tokens with Fourier Transforms paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the aESIM model in the Attention Boosted Sequential Inference Model paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Multi-task BiLSTM + Attn model in the GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Stacked Bi-LSTMs (shortcut connections, max-pooling) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the GenSen model in the Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Bi-LSTM sentence encoder (max-pooling) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the Stacked Bi-LSTMs (shortcut connections, max-pooling, attention) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SWEM-max model in the Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the MT-DNN-SMARTv0 model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the MT-DNN-SMART model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SMART+BERT-BASE model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the LM-CPPF RoBERTa-base model in the LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SMARTRoBERTa model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the SMART-BERT model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the MultiNLI dataset? | Matched, Mismatched, Accuracy, Dev Matched, Dev Mismatched |
What metrics were used to measure the roberta-base-mnli model in the Probing neural language models for understanding of words of estimative probability paper on the Probability words NLI dataset? | 1:1 Accuracy |
What metrics were used to measure the MacBERT-large model in the CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark paper on the KUAKE-QTR dataset? | Accuracy |
What metrics were used to measure the EFL model in the Entailment as Few-Shot Learner paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the EFL (Entailment as Few-shot Learner) + RoBERTa-large model in the Entailment as Few-Shot Learner paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the RoBERTa-large+Self-Explaining model in the Self-Explaining Structures Improve NLP Models paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the RoBERTa-large + self-explaining layer model in the Self-Explaining Structures Improve NLP Models paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the CA-MTL model in the Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the SemBERT model in the Semantics-aware BERT for Language Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN-SMARTLARGEv0 model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN model in the Multi-Task Deep Neural Networks for Natural Language Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the SJRC (BERT-Large +SRL) model in the Explicit Contextual Semantics for Text Comprehension paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
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