Stereotype detection at aequa-tech
Model Description
- Developed by: aequa-tech
- Funded by: NGI-Search
- Language(s) (NLP): Italian
- License: apache-2.0
- Finetuned from model: AlBERTo
This model is a fine-tuned version of AlBERTo Italian model on flame 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 2020 test sets (tweets and news headlines) obtaining the following results:
Metrics and Results
Tweets:
- macro F1: 0.81
- accuracy: 0.81
- precision of positive class: 0.77
- recall of positive class: 0.88
- F1 of positive class: 0.82
News Headlines:
- macro F1: 0.64
- accuracy: 0.73
- precision of positive class: 0.79
- recall of positive class: 0.33
- F1 of positive class: 0.47
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/flame-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")
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