Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
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How to use Arbi-Houssem/TunLangModel_test1.17 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test1.17") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test1.17")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test1.17", device_map="auto")This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3483 | 4.5045 | 500 | 1.0341 | 53.6221 |
| 0.1138 | 9.0090 | 1000 | 1.1225 | 49.9641 |
| 0.0476 | 13.5135 | 1500 | 1.1610 | 51.5278 |
| 0.0238 | 18.0180 | 2000 | 1.2585 | 48.0993 |
| 0.007 | 22.5225 | 2500 | 1.2873 | 51.6282 |
| 0.0021 | 27.0270 | 3000 | 1.2722 | 46.8656 |
| 0.0007 | 31.5315 | 3500 | 1.2998 | 43.5375 |
| 0.0006 | 36.0360 | 4000 | 1.3057 | 45.3307 |
Base model
openai/whisper-small