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hw2_text_finetune_distilbert – AI Model by george2cool36 | AlphaNeural AI
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hw2_text_finetune_distilbert
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transformers
safetensors
distilbert
text-classification
finetuned
homework
ddecosmo/hw_text_dataset
mit
text-embeddings-inference
endpoints_compatible
us
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HW 2 - DistilBERT fine-tuned
Task
Fine-tuned
DistilBERT
for text classification on a classmate's HW1 dataset.
Dataset:
ddecosmo/hw_text_dataset
Text column:
Text
Label column:
label
(classes: ['asu', 'bucknell', 'cmu', 'duq', 'ucsd'])
Train/Eval split: 80/20 (stratified if available)
Training
Base model:
distilbert-base-uncased
Epochs: 3, LR=5e-5, WD=0.01, warmup=10%
Batch size: 16
Best model by: F1 (macro)
Results (Test)
Accuracy: 0.4000
F1 (macro): 0.1231
Precision (macro): nan
Recall (macro): nan
Notes & Limitations
Small student dataset; results may vary with seeds.
Labels mapped as: {'asu': 0, 'bucknell': 1, 'cmu': 2, 'duq': 3, 'ucsd': 4}
AI Tool Disclosure
This notebook used ChatGPT for scaffolding code and documentation. All dataset selection, training, evaluation, and uploads were performed by the student.
