google/speech_commands
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How to use gokulsrinivasagan/whisper-small-diff-wo-continuous-ls-diff-enc-speech-commands-v1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="gokulsrinivasagan/whisper-small-diff-wo-continuous-ls-diff-enc-speech-commands-v1") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("gokulsrinivasagan/whisper-small-diff-wo-continuous-ls-diff-enc-speech-commands-v1")
model = AutoModelForAudioClassification.from_pretrained("gokulsrinivasagan/whisper-small-diff-wo-continuous-ls-diff-enc-speech-commands-v1")This model was trained from scratch on the speech_commands 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 | Accuracy |
|---|---|---|---|---|
| 0.1436 | 1.0 | 1236 | 1.3164 | 0.7896 |
| 0.1585 | 2.0 | 2472 | 1.2858 | 0.7990 |
| 0.109 | 3.0 | 3708 | 1.3847 | 0.7986 |
| 0.0708 | 4.0 | 4944 | 1.3932 | 0.7990 |
| 0.0481 | 5.0 | 6180 | 1.4563 | 0.8004 |