Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
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How to use Arbi-Houssem/TunLangModel_test1.9 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test1.9") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test1.9")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test1.9", device_map="auto")This model is a fine-tuned version of openai/whisper-base 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 |
|---|---|---|---|---|
| 0.5147 | 7.7519 | 500 | 3.1417 | 128.5618 |
| 0.0559 | 15.5039 | 1000 | 3.8111 | 132.5456 |
| 0.01 | 23.2558 | 1500 | 4.2115 | 120.1891 |
| 0.0029 | 31.0078 | 2000 | 4.4628 | 120.3916 |
| 0.0017 | 38.7597 | 2500 | 4.6127 | 111.2086 |
| 0.0011 | 46.5116 | 3000 | 4.6945 | 124.6455 |
| 0.0009 | 54.2636 | 3500 | 4.7426 | 113.3018 |
| 0.0009 | 62.0155 | 4000 | 4.7577 | 117.6907 |
Base model
openai/whisper-base