README.md

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: 0.9790777669399117
            name: Accuracy
            verified: true
            verifyToken: >-
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          - type: precision
            value: 0.9197835301644851
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.946479027789208
            name: Recall
            verified: true
            verifyToken: >-
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          - type: f1
            value: 0.9329403493591477
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.06360606849193573
            name: loss
            verified: true
            verifyToken: >-
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      - 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
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjY5OGMzNzg1Mjg4YmFlOWEwOGVkZmM2OTQwYTUyMzRmZWNiZjFmNmM0OGU0MmM2Y2YwZGM1M2EyNDg5NTNhYSIsInZlcnNpb24iOjF9.ttERWzOkI_iUeEzv63lMNYvzdlU0q3gbqYL41_ZjZ-VKrIVMgEfsZCN2ldPJWPZaPiW_UnrUpbBLFTPieIQ-Dw
          - type: precision
            value: 0.9339674814732883
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.9159344831326608
            name: Recall
            verified: true
            verifyToken: >-
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          - type: f1
            value: 0.9248630887185104
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.07593930512666702
            name: loss
            verified: true
            verifyToken: >-
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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)