Update README.md

README.md

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 # Whisper Medium EN Fine-Tuned for Air Traffic Control (ATC)
 
+## Deprecation Notice (August 24, 2025)
+
+This model is now **deprecated**. A newer and **larger, better-performing model** is available, achieving a **6.5% word error rate**, a significant improvement over the previous version (≈15.08% WER).
+
+[View the updated model on Hugging Face](https://huggingface.co/jacktol/whisper_large_v3_finetuned_6.5_eval_wer)
+
 ## Model Overview
 
 This model is a fine-tuned version of OpenAI's Whisper Medium EN model, specifically trained on **Air Traffic Control (ATC)** communication datasets. The fine-tuning process significantly improves transcription accuracy on domain-specific aviation communications, reducing the **Word Error Rate (WER) by 84%**, compared to the original pretrained model. The model is particularly effective at handling accent variations and ambiguous phrasing often encountered in ATC communications.
@@ -63,15 +69,6 @@ The fine-tuned Whisper model is designed for:
 
 You can test the model online using the [ATC Transcription Assistant](https://huggingface.co/spaces/jacktol/ATC-Transcription-Assistant), which lets you upload audio files and generate transcriptions.
 
-## Model Description
-
-Whisper Medium EN fine-tuned for ATC is optimized to handle short, distinct transmissions between pilots and air traffic controllers. It is fine-tuned using data from the **[ATC Dataset](https://huggingface.co/datasets/jacktol/atc-dataset)**, a combined and cleaned dataset sourced from the following:
-
-- **[ATCO2 corpus](https://huggingface.co/datasets/Jzuluaga/atco2_corpus_1h)** (1-hour test subset)
-- **[UWB-ATCC corpus](https://huggingface.co/datasets/Jzuluaga/uwb_atcc)**
-
-The **ATC Dataset** merges these two original sources, filtering and refining the data to enhance transcription accuracy for domain-specific ATC communications.
-
 ## Training Procedure
 
 - **Hardware**: Fine-tuning was conducted on two A100 GPUs with 80GB memory.