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
          - type: precision
            value: 0.9197835301644851
            name: Precision
            verified: true
          - type: recall
            value: 0.946479027789208
            name: Recall
            verified: true
          - type: f1
            value: 0.9329403493591477
            name: F1
            verified: true
          - type: loss
            value: 0.06360606849193573
            name: loss
            verified: true
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: acronym_identification
          type: acronym_identification
          config: default
          split: validation
        metrics:
          - type: accuracy
            value: 0.9758059763069488
            name: Accuracy
            verified: true
            verifyToken: >-
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          - type: precision
            value: 0.9339528708927979
            name: Precision
            verified: true
            verifyToken: >-
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          - type: recall
            value: 0.9157175398633257
            name: Recall
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjk5Mzk3MzRlYjg2ZWNmOTZlN2QwZjQ2Y2ZlNzU2NzljODU1NmRmNWVjMmIxODdhZTE4NmQwYTNkY2E2MGZlZSIsInZlcnNpb24iOjF9.JShPPAdznEKVso15qYmJ9OcdiV_W4pE1wrHVZ_A_-bkhboIUATN-rXK2KZmfq1nS3Jxip3qn9GYeFxP9tGU0Dg
          - type: f1
            value: 0.924745317121262
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.07582829147577286
            name: loss
            verified: true
            verifyToken: >-
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          - type: auc
            value: NaN
            name: AUC
            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)