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burkialisher5
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burkialisher5
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pashto-ghag-whisper-medium-asr)oru)WhisperForConditionalGeneration (Whisper Medium - 769M parameters)r=32, alpha=64, modules: q_proj, v_proj, k_proj, out_proj, fc1, fc2)| Model Version | Target Language | WER (%) | CER (%) | Delta WER vs Baseline |
|---|---|---|---|---|
| Zero-Shot Pashto Ghag Base | Ormuri (oru) | 84.86% | 37.08% | Baseline |
| Fine-Tuned Checkpoint 100 | Ormuri (oru) | 36.54% | 12.89% | -48.32 pp |
| Fine-Tuned Checkpoint 200 | Ormuri () |
python
import torchfrom transformers import pipeline # Initialize pipelineasr_pipeline = pipeline( "automatic-speech-recognition", model="burkialisher5/Ormuri_ASR", device="cuda" if torch.cuda.is_available() else "cpu", torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,) # Transcribe Ormuri audio fileresult = asr_pipeline("path/to/ormuri_sample.wav")print("Ormuri Transcription:", result["text"])python
import torchimport librosafrom transformers import WhisperProcessor, WhisperForConditionalGeneration device = "cuda" if torch.cuda.is_available() else "cpu" processor = WhisperProcessor.from_pretrained("burkialisher5/Ormuri_ASR")model = WhisperForConditionalGeneration.from_pretrained( "burkialisher5/Ormuri_ASR", torch_dtype=torch.float16 if device == "cuda" else torch.float32).to(device) # Load audio resampled to 16kHzaudio, sr = librosa.load("path/to/ormuri_sample.wav", sr=16000) input_features = processor(audio, sampling_rate=16000, return_tensors="pt").input_features.to(device)if device == "cuda": input_features = input_features.to(torch.float16) forced_decoder_ids = processor.get_decoder_prompt_ids(language="pashto", task="transcribe") with torch.no_grad(): predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids, max_new_tokens=225) transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]print("Ormuri Transcription:", transcription)lr=3e-4).pashto-ghag-whisper-medium-asr).oru| 25.78% |
| 8.35% |
| -59.08 pp |
| Fine-Tuned Checkpoint 300 | Ormuri (oru) | 23.18% | 7.29% | -61.68 pp |
| Fine-Tuned Checkpoint 400 | Ormuri (oru) | 20.44% | 6.41% | -64.42 pp |
| Fine-Tuned Checkpoint 600 (This Model) | Ormuri (oru) | 18.39% | 5.65% | -66.47 pp (Best) |