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Add evaluation results on the default config and train split of acronym_identification
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metadata
language: en
tags:
  - autotrain
datasets:
  - lewtun/autotrain-data-acronym-identification
  - acronym_identification
widget:
  - text: I love AutoTrain 🤗
co2_eq_emissions: 10.435358044493652
model-index:
  - name: autotrain-demo
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: acronym_identification
          type: acronym_identification
          args: default
        metrics:
          - type: accuracy
            value: 0.9708090976211485
            name: Accuracy
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: acronym_identification
          type: acronym_identification
          config: default
          split: train
        metrics:
          - type: accuracy
            value: 0.9790759837443896
            name: Accuracy
            verified: true
            verifyToken: >-
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          - type: precision
            value: 0.9198149678726638
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.9464104463281485
            name: Recall
            verified: true
            verifyToken: >-
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          - type: f1
            value: 0.9329232017306652
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.0635102167725563
            name: loss
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDc0MDU5MzMzMTE5ZGIxYTJiNDYxN2ExNDgwYTA2YjMxZGQzYjliNDRkZDgxMjRmOWNhYmUyMDUwOTc0ZDIzOCIsInZlcnNpb24iOjF9.2TI5fvK_-vuDXhuU2dQy_wLdJI6cFzah3dnIJGBXz-KjxNXlk80EwlTG6z5D67I6DL5gPrdLAcntj_1r45uqDg
          - type: auc
            value: NaN
            name: AUC
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTY5MjdlZjk1MzRiMzQ2MDJkODNlMzE0YzM4YWZlOGYwN2RhMGYxMGRmOTk0MjZmZDU0ZGNhOTZiMzk5NGQyZSIsInZlcnNpb24iOjF9.brkCtVbx4JLv4qx_fWoNywrCerV_uxjMuItJB78dAzv0OBMS6yq-78I2yYNS9acUGBNmlOcTDzxpg_oZEe0zCA
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: acronym_identification
          type: acronym_identification
          config: default
          split: validation
        metrics:
          - type: accuracy
            value: 0.9758354452761242
            name: Accuracy
            verified: true
          - type: precision
            value: 0.9339674814732883
            name: Precision
            verified: true
          - type: recall
            value: 0.9159344831326608
            name: Recall
            verified: true
          - type: f1
            value: 0.9248630887185104
            name: F1
            verified: true
          - type: loss
            value: 0.07593930512666702
            name: loss
            verified: true

Model Trained Using AutoTrain

  • Problem type: Entity Extraction
  • Model ID: 7324788
  • CO2 Emissions (in grams): 10.435358044493652

Validation Metrics

  • Loss: 0.08991389721632004
  • Accuracy: 0.9708090976211485
  • Precision: 0.8998421675654347
  • Recall: 0.9309429854401959
  • F1: 0.9151284109149278

Usage

You can use cURL to access this model:

$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/lewtun/autotrain-acronym-identification-7324788

Or Python API:

from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lewtun/autotrain-acronym-identification-7324788", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)