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Distilbert Base Uncased Becas 1
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Distilbert Base Uncased Becas 1
Developed by Evelyn18
A text classification model fine-tuned on the becasv2 dataset based on distilbert-base-uncased
Downloads 18
Release Time : 6/29/2022
Model Overview
This model is a fine-tuned version of DistilBERT, primarily used for text classification tasks. Trained on the becasv2 dataset with a validation loss of 3.8655.
Model Features
Efficient and Lightweight
Based on the DistilBERT architecture, more lightweight and efficient than standard BERT models
Fine-tuning Optimization
Fine-tuned on a specific dataset (becasv2), potentially offering better performance for domain-specific tasks
Model Capabilities
Text Classification
Natural Language Understanding
Use Cases
Text Analysis
Text Classification
Can be used to classify English texts
Validation loss 3.8655
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