stereotype-it / README.md
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metadata
license: apache-2.0
metrics:
  - accuracy
  - f1
pipeline_tag: text-classification
tags:
  - stereotype
language:
  - it

Stereotype detection at aequa-tech

Model Description

This model is a fine-tuned version of AlBERTo Italian model on stereotypes detection

Training Details

Training Data

Training Hyperparameters

  • learning_rate: 2e-5
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam

Evaluation

Testing Data

It was tested on HaSpeeDe test sets (tweets and news headlines) obtaining the following results:

Metrics and Results

Tweets:

  • macro F1: 0.75
  • accuracy: 0.75
  • precision of positive class: 0.66
  • recall of positive class: 0.94
  • F1 of positive class: 0.78

News Headlines:

  • macro F1: 0.72
  • accuracy: 0.77
  • precision of positive class: 0.73
  • recall of positive class: 0.52
  • F1 of positive class: 0.61

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.1.2
  • Datasets 2.19.0
  • Accelerate 0.30.0

How to use this model:

model = AutoModelForSequenceClassification.from_pretrained('aequa-tech/stereotype-it',num_labels=2) 
tokenizer = AutoTokenizer.from_pretrained("m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0") 
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
classifier("text")