# Efficient text understanding

This is a Bert model optimized for Turkish, specifically designed for text classification tasks in the logistics domain.

DistilBERT is a lightweight distilled version of BERT, retaining most of BERT's performance but with fewer parameters and faster inference speed.

A RoBERTa base model pre-trained on 1B tokens with a validation perplexity of 3.93, suitable for English text processing tasks.

ALBERT Small v2 is a 6-layer lightweight version of ALBERT-base-v2, based on the Transformer architecture, suitable for natural language processing tasks.

A RoBERTa model pretrained on a small-scale dataset of 1M tokens, using the MED-SMALL architecture, suitable for text understanding tasks.