infinite-learning-station/whisper_indian_restaurant_training
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How to use infinite-learning-station/whisper-tiny-indian-restaurant with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="infinite-learning-station/whisper-tiny-indian-restaurant") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("infinite-learning-station/whisper-tiny-indian-restaurant")
model = AutoModelForSpeechSeq2Seq.from_pretrained("infinite-learning-station/whisper-tiny-indian-restaurant")This model is a fine-tuned version of openai/whisper-tiny on the Indian Restaurant Orders 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 |
|---|---|---|---|---|
| 0.0954 | 0.9893 | 1200 | 0.0963 | 17.5894 |
| 0.0765 | 1.9786 | 2400 | 0.0794 | 16.6739 |
| 0.0658 | 2.9678 | 3600 | 0.0725 | 15.8521 |
| 0.0627 | 3.9571 | 4800 | 0.0665 | 15.2682 |
| 0.0505 | 4.9464 | 6000 | 0.0648 | 14.4968 |
| 0.0471 | 5.9357 | 7200 | 0.0613 | 13.9129 |
| 0.0404 | 6.9250 | 8400 | 0.0600 | 13.3218 |
| 0.0323 | 7.9143 | 9600 | 0.0600 | 12.9181 |
| 0.0289 | 8.9035 | 10800 | 0.0592 | 12.7235 |
| 0.0251 | 9.8928 | 12000 | 0.0593 | 12.9686 |
Base model
openai/whisper-tiny