readme: ---
  tags:
  - mteb
  model-index:
  - name: random_embedding
    results:
    - task:
        type: Classification
      dataset:
        type: mteb/amazon_counterfactual
        name: MTEB AmazonCounterfactualClassification (en)
        config: en
        split: test
        revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      metrics:
      - type: accuracy
        value: 72.76119402985076
      - type: ap
        value: 35.34748033621631
      - type: f1
        value: 66.69148523181609
    - task:
        type: Classification
      dataset:
        type: mteb/amazon_counterfactual
        name: MTEB AmazonCounterfactualClassification (de)
        config: de
        split: test
        revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      metrics:
      - type: accuracy
        value: 70.35331905781584
      - type: ap
        value: 82.06081447005229
      - type: f1
        value: 68.8136026256973
    - task:
        type: Classification
      dataset:
        type: mteb/amazon_counterfactual
        name: MTEB AmazonCounterfactualClassification (en-ext)
        config: en-ext
        split: test
        revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      metrics:
      - type: accuracy
        value: 73.61319340329835
      - type: ap
        value: 21.00160415169939
      - type: f1
        value: 60.10560516308614
    - task:
        type: Classification
      dataset:
        type: mteb/amazon_counterfactual
        name: MTEB AmazonCounterfactualClassification (ja)
        config: ja
        split: test
        revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      metrics:
      - type: accuracy
        value: 65.54603854389721
      - type: ap
        value: 15.077369983612456
      - type: f1
        value: 52.497988427862886
    - task:
        type: Classification
      dataset:
        type: mteb/amazon_polarity
        name: MTEB AmazonPolarityClassification
        config: default
        split: test
        revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      metrics:
      - type: accuracy
        value: 55.73870000000001
      - type: ap
        value: 53.340829136283844
      - type: f1
        value: 54.918240496528384
    - task:
        type: Classification
      dataset:
        type: mteb/banking77
        name: MTEB Banking77Classification
        config: default
        split: test
        revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      metrics:
      - type: accuracy
        value: 60.230519480519476
      - type: f1
        value: 60.35369520728743
    - task:
        type: Classification
      dataset:
        type: mteb/emotion
        name: MTEB EmotionClassification
        config: default
        split: test
        revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
      metrics:
      - type: accuracy
        value: 20.115000000000002
      - type: f1
        value: 18.226328500457676
    - task:
        type: Classification
      dataset:
        type: mteb/imdb
        name: MTEB ImdbClassification
        config: default
        split: test
        revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      metrics:
      - type: accuracy
        value: 53.825599999999994
      - type: ap
        value: 52.10683421279975
      - type: f1
        value: 52.92972152632716
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (en)
        config: en
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 70.81167350661197
      - type: f1
        value: 70.00020062179125
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (de)
        config: de
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 70.4733727810651
      - type: f1
        value: 67.5573662659563
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (es)
        config: es
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 73.54569713142095
      - type: f1
        value: 71.0893535642869
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (fr)
        config: fr
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 66.56122768556217
      - type: f1
        value: 62.695886045141236
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (hi)
        config: hi
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 40.98960200788813
      - type: f1
        value: 40.41755880161599
    - task:
        type: Classification
      dataset:
        type: mteb/mtop_domain
        name: MTEB MTOPDomainClassification (th)
        config: th
        split: test
        revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      metrics:
      - type: accuracy
        value: 15.72875226039783
      - type: f1
       