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BERTimbau-CEFR
joaoDossena/BERTimbau-CEFR
BERTimbau-CEFR is a machine learning model from joaoDossena. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
BERTimbau-CEFR is a fine-tuned version of BERTimbau for the task of classifiying text difficulty in Portuguese in the CEFR scale.
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Updated Dec 23, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Oct 2, 2023
- Updated
- Dec 23, 2024
- SHA
- 08a934ae
Model card
From the Hugging Face model README
Introduction
BERTimbau-CEFR is a fine-tuned version of BERTimbau for the task of classifiying text difficulty in Portuguese in the CEFR scale.
It's based on bert-base-portuguese-cased, which has 12 layers and 110M parameters, and was fine-tuned on the COPLE2 corpus (Mendes et al. [2016]). BERTimbau-CEFR was developed in the context of the Master's thesis "Learning What to Learn: Generating Language Lessons using BERT", whose repository with code and text is available on Github.
Usage
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
labels = ["A1", "A2", "B1", "B2", "C1"]
checkpoint = 'neuralmind/bert-base-portuguese-cased'
model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=len(labels))
tokenizer = AutoTokenizer.from_pretrained(checkpoint, do_lower_case=False)
checkpoint = torch.load("model_4_acc86%")
model.load_state_dict(checkpoint)
- License
- mit
- Languages
- pt
- Created
- Oct 2, 2023
- Updated
- Dec 23, 2024