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albert-act-tiny

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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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+
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+ model-index:
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+ - name: asi/albert-act-base
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+ results:
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+ - task:
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+ type: text-classification
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+ name: CoLA
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+ dataset:
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+ type: glue
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+ name: CoLA # General Language Understanding Evaluation benchmark (GLUE)
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+ split: cola
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+ metrics:
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+ - type: matthews_correlation
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+ value: 27.5
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+ name: Matthew's Corr
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+ - task:
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+ type: text-classification
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+ name: SST-2
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+ dataset:
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+ type: glue
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+ name: SST-2 # The Stanford Sentiment Treebank
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+ split: sst2
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+ metrics:
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+ - type: accuracy
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+ value: 87.6
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: MRPC
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+ dataset:
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+ type: glue
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+ name: MRPC # Microsoft Research Paraphrase Corpus
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+ split: mrpc
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+ metrics:
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+ - type: accuracy
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+ value: 78.7
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+ name: Accuracy
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+ - type: f1
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+ value: 84.7
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+ name: F1
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+ - task:
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+ type: text-similarity
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+ name: STS-B
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+ dataset:
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+ type: glue
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+ name: STS-B # Semantic Textual Similarity Benchmark
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+ split: stsb
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+ metrics:
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+ - type: spearmanr
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+ value: 79.7
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+ name: Spearman Corr
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+ - type: pearsonr
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+ value: 81.8
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+ name: Pearson Corr
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+ - task:
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+ type: text-classification
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+ name: QQP
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+ dataset:
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+ type: glue
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+ name: QQP # Quora Question Pairs
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+ split: qqp
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+ metrics:
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+ - type: f1
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+ value: 67.8
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+ name: F1
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+ - type: accuracy
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+ value: 87.5
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: MNLI-m
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+ dataset:
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+ type: glue
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+ name: MNLI-m # MultiNLI Matched
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+ split: mnli_matched
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+ metrics:
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+ - type: accuracy
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+ value: 77.0
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: MNLI-mm
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+ dataset:
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+ type: glue
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+ name: MNLI-mm # MultiNLI Matched
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+ split: mnli_mismatched
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+ metrics:
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+ - type: accuracy
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+ value: 76.8
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: QNLI
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+ dataset:
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+ type: glue
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+ name: QNLI # Question NLI
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+ split: qnli
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+ metrics:
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+ - type: accuracy
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+ value: 86.4
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: RTE
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+ dataset:
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+ type: glue
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+ name: RTE # Recognizing Textual Entailment
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+ split: rte
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+ metrics:
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+ - type: accuracy
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+ value: 62.0
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+ name: Accuracy
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+ - task:
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+ type: text-classification
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+ name: WNLI
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+ dataset:
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+ type: glue
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+ name: WNLI # Winograd NLI
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+ split: wnli
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+ metrics:
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+ - type: accuracy
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+ value: 65.1
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+ name: Accuracy
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