Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
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How to use Arbi-Houssem/TunLangModel_test1.15 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test1.15") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test1.15")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test1.15", 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 |
|---|---|---|---|---|
| 1.7779 | 4.5045 | 500 | 1.7860 | 89.0690 |
| 1.3825 | 9.0090 | 1000 | 1.4590 | 75.6419 |
| 1.2777 | 13.5135 | 1500 | 1.3650 | 72.4573 |
| 1.255 | 18.0180 | 2000 | 1.3039 | 68.0247 |
| 1.1248 | 22.5225 | 2500 | 1.2712 | 65.4139 |
| 1.0907 | 27.0270 | 3000 | 1.2522 | 62.5448 |
| 1.0969 | 31.5315 | 3500 | 1.2418 | 62.2579 |
| 1.111 | 36.0360 | 4000 | 1.2386 | 62.7026 |
Base model
openai/whisper-small