metadata

tags:
  - autotrain
  - text-classification
language:
  - en
widget:
  - text: >-
      a favourite dutch salad in the way some prime kippered herrings a dn d
      haddock or some fine yarmouth bloaters then when cold remove all the bones
      and skin aryl tear the flesh into shreds with two forks sea en these well
      with pepper salad oil and tarragea vinegar and set aside in a cool place
      until required cut up into small dice myrtle boil beetroot and potatoes
      raw cucumber and onions and mix well together with the fish and sonto
      wellmade tartar sauce then pile up the whols on a flat dish sprinkle well
      with a mixture of finelychopped parsley and sifted egg yolk garnish round
      the base with anchovy or saniino crodtons tastefully ornamented with tiny
      patches or chopped parsley and strips of hardboiled white of egg and servo
  - text: >-
      collieries the men at one of the collieries have in times of scarcity been
      in the habit houseo f this getting from e v i t a a t t el s eve r a
      wellnt wishing g h e t r h e a r v e als water disturbed so frequently
      locked up the well one of the men a blacksmith removed fhe lock and subse
      quently received notice to leave the colliery the other mechanics decided
      that unless the the masters at once withdrew the blacksmiths notice they
      themselves would resign the masters however refused and a fortni
datasets:
  - davanstrien/autotrain-data-recipes
co2_eq_emissions:
  emissions: 6.990639915807625

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 2451975973
CO2 Emissions (in grams): 6.9906

Validation Metrics

Loss: 0.046
Accuracy: 0.989
Macro F1: 0.936
Micro F1: 0.989
Weighted F1: 0.989
Macro Precision: 0.929
Micro Precision: 0.989
Weighted Precision: 0.989
Macro Recall: 0.943
Micro Recall: 0.989
Weighted Recall: 0.989

Usage

This model has been trained to predict whether an article from a historic newspaper is a 'recipe' or 'not a recipe'. This model was trained on data generated by carrying out a keyword search of food terms and annotating examples results to indicate whether they were a recipe.

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/davanstrien/autotrain-recipes-2451975973

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-recipes-2451975973", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-recipes-2451975973", use_auth_token=True)

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

outputs = model(**inputs)