Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
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How to use Arbi-Houssem/TunLangModel_test1.10 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test1.10") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test1.10")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test1.10", device_map="auto")This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0 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 |
|---|---|---|---|---|
| 1.6852 | 3.8760 | 500 | 3.5237 | 148.8184 |
| 1.2494 | 7.7519 | 1000 | 3.2200 | 121.6070 |
| 1.2202 | 11.6279 | 1500 | 3.1493 | 125.3883 |
| 1.0905 | 15.5039 | 2000 | 3.1099 | 113.9095 |
| 1.0606 | 19.3798 | 2500 | 3.0905 | 110.1958 |
| 1.0858 | 23.2558 | 3000 | 3.0846 | 109.9932 |
Base model
openai/whisper-small