mazkooleg/digit_mask_augmented_raw
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How to use mazkooleg/digit-mask-hubert-base-ls960-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="mazkooleg/digit-mask-hubert-base-ls960-ft") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("mazkooleg/digit-mask-hubert-base-ls960-ft")
model = AutoModelForAudioClassification.from_pretrained("mazkooleg/digit-mask-hubert-base-ls960-ft")This model is a fine-tuned version of facebook/hubert-base-ls960 on the None 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 | Accuracy | F1 | Validation Loss |
|---|---|---|---|---|---|
| 0.0094 | 1.0 | 14264 | 0.9985 | 0.9985 | 0.0087 |
| 0.0007 | 2.0 | 28528 | 0.9987 | 0.9987 | 0.0078 |
| 0.0008 | 3.0 | 42792 | 0.9987 | 0.9987 | 0.0101 |