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README.md

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+---
+tags:
+- text-to-image
+- lora
+- diffusers
+- template:diffusion-lora
+widget:
+- output:
+    url: images/Screenshot from 2025-08-20 00-50-33.png
+  text: None
+  parameters:
+    negative_prompt: None
+base_model: ProsusAI/finbert
+instance_prompt: null
+license: other
+license_name: useless
+license_link: LICENSE
+---
+# Emotion
+
+<Gallery />
+
+## Model description 
+
+Emotion Recognition Model (BERT-based)
+📌 Overview
+
+This is a BERT-based emotion recognition model that I created purely for educational and learning purposes.
+The model was trained as part of my journey to understand transformers, distillation, GPU management, fine-tuning, and Hugging Face workflows.
+
+⚙️ How I built it
+
+I started with a pretrained BERT model.
+
+I experimented with layer distillation (copying a few layers into a smaller student model).
+
+I trained it on an emotion classification dataset to predict different emotional states from text.
+
+I focused on hands-on practice: learning about tokenization, GPU memory issues, checkpointing, and model saving&#x2F;loading.
+
+⚠️ Disclaimer
+
+This model is not production-ready.
+
+It is not optimized for real-world use.
+
+It should not be used for commercial, fine-tuning, or deployment purposes.
+
+It was built only as a learning exercise to explore Hugging Face and model training.
+
+💡 Purpose
+
+To help me (and maybe others) understand how Hugging Face works.
+
+To practice model distillation and fine-tuning techniques.
+
+To learn the workflow of pushing models to Hugging Face Hub.
+
+🚫 Limitations
+
+Accuracy and reliability are not guaranteed.
+
+Not suitable for critical applications (mental health, customer service, etc.).
+
+Limited number of layers and trained on a small dataset.
+
+
+## Download model
+
+
+[Download](/Abdullah6395/Text_Emotion_Recognition/tree/main) them in the Files & versions tab.