MahmoudAshraf
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acft-whisper-large-v3-turbo

Automatic Speech Recognition

Safetensors

whisper

Eval Results

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 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+license: apache-2.0
+base_model:
+- openai/whisper-large-v3-turbo
+pipeline_tag: automatic-speech-recognition
+model-index:
+  - name: MahmoudAshraf/acft-whisper-large-v3-turbo
+    results:
+      - task:
+          type: automatic-speech-recognition
+        dataset:
+          name: distil-whisper/earnings22
+          type: distil-whisper/earnings22
+        metrics:
+          - name: WER
+            type: WER
+            value: 15.605
 ---
+# Model Card
+## Model Description
+This is in a fine-tuned series of [OpenAI's Whisper models](https://github.com/openai/whisper).
+The models have been finetuned for dynamic audio context robustness, allowing shorter audio contexts for better performance with short audio inputs. The method is detailed [in our GitHub repo](https://github.com/futo-org/whisper-acft).
+- **Developed by:** Mahmoud Ashraf inspired by FUTO
+- **License:** Apache-2.0
+- **Finetuned from model:** OpenAI Whisper
 ## Uses
+These models are not useful by themselves under default Whisper runtime configurations.
+The easiest way to test differing audio context is to use whisper.cpp with the `--audio-context` parameter. We provide converted whisper.cpp models in our [GitHub README](https://github.com/futo-org/whisper-acft?tab=readme-ov-file#finetuning-whisper-for-dynamic-audio-context-robustness).
+## Metrics
+Speed was evaluated using TensorRT-LLM using In-flight Batching
+| Model Name                                                       | WER on Earnings22    | Relative Speed |
+|------------------------------------------------------------------|--------|----------------|
+| Large-V3 Full Context                                            | 15.283 | 1.0x           |
+| Large-V3 Dynamic Context                                         | 17.515 | 2.1x           |
+| [MahmoudAshraf/acft-whisper-large-v3](https://huggingface.co/MahmoudAshraf/acft-whisper-large-v3)   | 15.381 | 2.1x           |
+| Large-V3 Turbo Full Context                                      | 15.373 | 1.9x           |
+| Large-V3 Turbo Dynamic Context                                      | 62.921 | 6.4x           |
+| This Model | 15.605 | 5.1x           |
+## Other Information
+More information can be found in this [GitHub README](https://github.com/futo-org/whisper-acft?tab=readme-ov-file#finetuning-whisper-for-dynamic-audio-context-robustness).