Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
Viewer • Updated • 1.1k • 18
How to use Arbi-Houssem/TunLangModel_test1.16 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test1.16") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test1.16")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test1.16", 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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.2076 | 4.5045 | 500 | 2.1992 | 120.4131 |
| 2.0416 | 9.0090 | 1000 | 2.0813 | 117.6732 |
| 1.9182 | 13.5135 | 1500 | 1.9770 | 119.2368 |
| 1.9273 | 18.0180 | 2000 | 1.9219 | 104.0023 |
| 1.8201 | 22.5225 | 2500 | 1.8901 | 94.8931 |
| 1.7708 | 27.0270 | 3000 | 1.8667 | 92.9709 |
| 1.7865 | 31.5315 | 3500 | 1.8565 | 90.8908 |
| 1.805 | 36.0360 | 4000 | 1.8540 | 90.7904 |
Base model
openai/whisper-small