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wetey/MARBERT-LHSAB
MARBERT-LHSAB is a text classification model from wetey. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
This model is part of the work done in <!-- add paper name --. <br The full code can be found at https://github.com/wetey/cluster-errors
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From the Hugging Face model README
This model is part of the work done in <!-- add paper name -->. <br> The full code can be found at https://github.com/wetey/cluster-errors
Use the code below to get started with the model.
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="wetey/MARBERT-LHSAB")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("wetey/MARBERT-LHSAB")
model = AutoModelForSequenceClassification.from_pretrained("wetey/MARBERT-LHSAB")
This model is fine-tuned on the L-HSAB. The exact version we use (after removing duplicates) can be found . <!--TODO-->
The exact fine-tuning procedure followed can be found here
evaluation_strategy = 'epoch'
logging_steps = 1,
num_train_epochs = 5,
learning_rate = 1e-5,
eval_accumulation_steps = 2
Test set used can be found here
accuracy: 87.9% <br>
precision: 88.1% <br>
recall: 87.9% <br>
f1-score: 87.9% <br>
| Label | Precision | Recall | F1-score |
|---|---|---|---|
| normal | 85% | 82% | 83% |
| abusive | 93% | 92% | 93% |
| hate | 68% | 78% | 72% |