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language:
  - multilingual
license: apache-2.0
tags:
  - echo-dsrn
  - intent-classification
  - multilingual
  - massive
  - recurrent-neural-network
  - sklearn-initialized
datasets:
  - AmazonScience/massive
metrics:
  - accuracy
pipeline_tag: text-classification
base_model: ethicalabs/Echo-DSRN-v0.1.3-Embed-Intent
model-index:
  - name: Echo-DSRN-v0.1.4-Embed-Intent-CLF
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (af)
          config: af
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7505
          - type: f1
            value: 0.6939
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (am)
          config: am
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6925
          - type: f1
            value: 0.6323
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ar)
          config: ar
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6869
          - type: f1
            value: 0.6268
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (az)
          config: az
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7654
          - type: f1
            value: 0.7086
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (bn)
          config: bn
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7068
          - type: f1
            value: 0.6407
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (cy)
          config: cy
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7567
          - type: f1
            value: 0.6957
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (da)
          config: da
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7692
          - type: f1
            value: 0.7032
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (de)
          config: de
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7442
          - type: f1
            value: 0.6713
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (el)
          config: el
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7392
          - type: f1
            value: 0.6847
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7913
          - type: f1
            value: 0.7305
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (es)
          config: es
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7617
          - type: f1
            value: 0.7087
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fa)
          config: fa
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7443
          - type: f1
            value: 0.6782
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fi)
          config: fi
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7358
          - type: f1
            value: 0.674
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fr)
          config: fr
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7644
          - type: f1
            value: 0.7023
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (he)
          config: he
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7359
          - type: f1
            value: 0.6813
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hi)
          config: hi
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7387
          - type: f1
            value: 0.6707
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hu)
          config: hu
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7276
          - type: f1
            value: 0.6695
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hy)
          config: hy
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.719
          - type: f1
            value: 0.6579
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (id)
          config: id
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7823
          - type: f1
            value: 0.7208
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (is)
          config: is
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7501
          - type: f1
            value: 0.6931
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (it)
          config: it
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7756
          - type: f1
            value: 0.7269
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ja)
          config: ja
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7672
          - type: f1
            value: 0.7134
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (jv)
          config: jv
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7493
          - type: f1
            value: 0.6784
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ka)
          config: ka
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6762
          - type: f1
            value: 0.6286
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (km)
          config: km
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6288
          - type: f1
            value: 0.5668
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (kn)
          config: kn
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6553
          - type: f1
            value: 0.6085
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ko)
          config: ko
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7528
          - type: f1
            value: 0.7032
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (lv)
          config: lv
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7456
          - type: f1
            value: 0.699
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ml)
          config: ml
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7236
          - type: f1
            value: 0.6557
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (mn)
          config: mn
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7463
          - type: f1
            value: 0.6933
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ms)
          config: ms
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7727
          - type: f1
            value: 0.7234
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (my)
          config: my
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7024
          - type: f1
            value: 0.6442
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (nb)
          config: nb
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7672
          - type: f1
            value: 0.7048
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (nl)
          config: nl
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7673
          - type: f1
            value: 0.6953
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (pl)
          config: pl
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7562
          - type: f1
            value: 0.706
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (pt)
          config: pt
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7814
          - type: f1
            value: 0.7256
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ro)
          config: ro
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7544
          - type: f1
            value: 0.6861
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ru)
          config: ru
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7439
          - type: f1
            value: 0.6855
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (sl)
          config: sl
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7341
          - type: f1
            value: 0.6819
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (sq)
          config: sq
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7545
          - type: f1
            value: 0.6993
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (sv)
          config: sv
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7654
          - type: f1
            value: 0.7029
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (sw)
          config: sw
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7375
          - type: f1
            value: 0.6863
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ta)
          config: ta
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7085
          - type: f1
            value: 0.6461
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (te)
          config: te
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.6683
          - type: f1
            value: 0.6169
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (th)
          config: th
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7188
          - type: f1
            value: 0.6896
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (tl)
          config: tl
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7602
          - type: f1
            value: 0.7016
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (tr)
          config: tr
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7505
          - type: f1
            value: 0.6918
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ur)
          config: ur
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7193
          - type: f1
            value: 0.6559
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (vi)
          config: vi
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7592
          - type: f1
            value: 0.7036
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (zh-CN)
          config: zh-CN
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7528
          - type: f1
            value: 0.6987
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (zh-TW)
          config: zh-TW
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
        metrics:
          - type: accuracy
            value: 0.7322
          - type: f1
            value: 0.6915
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (af)
          config: af
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8157
          - type: f1
            value: 0.8077
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (am)
          config: am
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7625
          - type: f1
            value: 0.7488
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ar)
          config: ar
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7672
          - type: f1
            value: 0.759
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (az)
          config: az
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8268
          - type: f1
            value: 0.8188
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (bn)
          config: bn
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7834
          - type: f1
            value: 0.773
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (cy)
          config: cy
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8185
          - type: f1
            value: 0.8105
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (da)
          config: da
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8242
          - type: f1
            value: 0.8123
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (de)
          config: de
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8235
          - type: f1
            value: 0.8133
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (el)
          config: el
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7986
          - type: f1
            value: 0.7886
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8407
          - type: f1
            value: 0.8375
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (es)
          config: es
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8298
          - type: f1
            value: 0.8211
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (fa)
          config: fa
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8081
          - type: f1
            value: 0.7963
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (fi)
          config: fi
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7982
          - type: f1
            value: 0.788
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (fr)
          config: fr
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8275
          - type: f1
            value: 0.8199
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (he)
          config: he
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7959
          - type: f1
            value: 0.7808
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (hi)
          config: hi
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8022
          - type: f1
            value: 0.7919
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (hu)
          config: hu
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7978
          - type: f1
            value: 0.7883
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (hy)
          config: hy
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7892
          - type: f1
            value: 0.7793
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (id)
          config: id
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8379
          - type: f1
            value: 0.8269
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (is)
          config: is
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8154
          - type: f1
            value: 0.8085
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (it)
          config: it
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8277
          - type: f1
            value: 0.819
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ja)
          config: ja
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8302
          - type: f1
            value: 0.8245
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (jv)
          config: jv
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8163
          - type: f1
            value: 0.8135
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ka)
          config: ka
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7621
          - type: f1
            value: 0.7508
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (km)
          config: km
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7279
          - type: f1
            value: 0.7065
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (kn)
          config: kn
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7474
          - type: f1
            value: 0.7358
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ko)
          config: ko
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8145
          - type: f1
            value: 0.8065
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (lv)
          config: lv
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8076
          - type: f1
            value: 0.8029
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ml)
          config: ml
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7899
          - type: f1
            value: 0.7754
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (mn)
          config: mn
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8045
          - type: f1
            value: 0.7898
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ms)
          config: ms
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8262
          - type: f1
            value: 0.8183
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (my)
          config: my
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7772
          - type: f1
            value: 0.7633
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nb)
          config: nb
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8223
          - type: f1
            value: 0.8135
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nl)
          config: nl
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8298
          - type: f1
            value: 0.8192
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pl)
          config: pl
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8139
          - type: f1
            value: 0.802
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pt)
          config: pt
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8281
          - type: f1
            value: 0.8226
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ro)
          config: ro
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.813
          - type: f1
            value: 0.8033
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ru)
          config: ru
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8088
          - type: f1
            value: 0.8029
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sl)
          config: sl
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7976
          - type: f1
            value: 0.7947
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sq)
          config: sq
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8154
          - type: f1
            value: 0.8054
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sv)
          config: sv
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8245
          - type: f1
            value: 0.8178
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sw)
          config: sw
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8101
          - type: f1
            value: 0.8006
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ta)
          config: ta
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7846
          - type: f1
            value: 0.7729
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (te)
          config: te
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7478
          - type: f1
            value: 0.7392
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (th)
          config: th
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.7999
          - type: f1
            value: 0.7888
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tl)
          config: tl
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8187
          - type: f1
            value: 0.813
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tr)
          config: tr
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8088
          - type: f1
            value: 0.8001
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ur)
          config: ur
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.793
          - type: f1
            value: 0.7806
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (vi)
          config: vi
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8118
          - type: f1
            value: 0.8077
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-CN)
          config: zh-CN
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8139
          - type: f1
            value: 0.8039
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-TW)
          config: zh-TW
          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
        metrics:
          - type: accuracy
            value: 0.8096
          - type: f1
            value: 0.8028
library_name: transformers

Model Card for ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF

Architecture graph for ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF. Open in hfviewer

60-class multilingual intent classifier built on ethicalabs/Echo-DSRN-v0.1.3-Embed-Intent.

Uses mean_c_all pooling on the DSRN recurrent slow state (2048-dim), followed by a linear classification head initialized via sklearn SGDClassifier (86.49% training accuracy on 1.78M MASSIVE utterances) and refined with cross-entropy fine-tuning.

Architecture: EchoForSequenceClassification — Dual-State Recurrent Neural Network (DSRN) backbone with linear classification head.

Two paths to build an Echo classifier

Echo-DSRN supports two distinct classifier construction paths:

Path 1: Causal LM → Classifier (`from_causal_lm`)

Used by v0.1.3-Intent-CLF. Builds on a generative backbone:

Pooling: Last-token hidden state (768-dim fast state)
Inference: Chat template required (system_prompt + user_template baked into config)
Training: Frozen backbone → sklearn LogisticRegression → copy weights → no further fine-tuning
Strength: Exploits LM-trained surface-form features

Path 2: Embedding → Classifier (`from_embedding`) ← this model

Built on v0.1.3-Embed-Intent:

Pooling: Mean of recurrent slow states c_all (2048-dim)
Inference: Raw text — no chat template (classification_use_chat_template: false)
Training: Sklearn SGDClassifier init (86.49% train acc) + cross-entropy fine-tuning
Strength: Cross-lingual consistency from MNRL-trained embedding space

Training

Base: ethicalabs/Echo-DSRN-v0.1.3-Embed-Intent
Conversion: EchoForSequenceClassification.from_embedding() with random init
Sklearn init: SGDClassifier on precomputed 2048-dim mean_c_all embeddings (1.78M samples, 86.49% training accuracy)
CE fine-tuning: 5 epochs, batch_size=32, lr=2e-5, cosine schedule
Dataset: Amazon MASSIVE, all 51 locales

Example Usage

from transformers import pipeline
pipe = pipeline("text-classification", model="ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF", trust_remote_code=True, device="cpu")
sentences = [
    "I will file a police report if there is pineapple on this pizza.",
    "One Margherita pizza, and strictly no pineapples, thanks.",
    "Fun fact: Pineapples take almost two years to grow."
]
predictions = pipe.predict(sentences)
print(predictions)

Output

[{'label': 'general_quirky', 'score': 0.44068652391433716}, {'label': 'takeaway_order', 'score': 0.6128405332565308}, {'label': 'general_quirky', 'score': 0.9770827293395996}]

What the model is thinking:

"I will file a police report if there is pineapple on this pizza." -> general_quirky (44%)
- The Model: "There is a 44% chance this person is making a quirky joke, but I am also detecting a strong undercurrent of genuine hostility toward tropical fruit. I am not entirely sure if this is a pizza order or a legal threat."
- (Note: It misses takeaway_order here because the slow state gets overwhelmed by the high-entropy threat of police involvement.)
"One Margherita pizza, and strictly no pineapples, thanks." -> takeaway_order (61%)
- The Model: "A polite, standard transaction. No drama, just dough. Solid takeaway_order intent."
"Fun fact: Pineapples take almost two years to grow." -> general_quirky (97%)
- The Model: "Ah, unprompted trivia. 97% confidence that this user is just being weird and definitely does not want a pizza."

Results

Classification

Benchmarked on the MASSIVE en-US validation subset (100 samples): 79% accuracy via classify().

The model uses raw text — no chat template (classification_use_chat_template: false in config).

Post-CE Embedding Quality (MTEB)

After CE fine-tuning, the classifier backbone was extracted (discarding the classification head) and evaluated via MTEB's logistic regression protocol onfrozen embeddings.

Compared to the original embedding model:

Task	Original Embed-Intent	Post-CE Backbone	Δ
MassiveIntentClassification (51 langs)	72.42%	73.90%	+1.48
MassiveScenarioClassification (51 langs)	79.00%	80.48%	+1.48

The identical +1.48 improvement on both independently-evaluated tasks confirms a systematic improvement: CE fine-tuning pushed the backbone clusters to maximize class separation, and the structural improvement survived removal of the fine-tuned classification head.