mazkooleg/digit_mask_augmented_raw
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How to use mazkooleg/digit-mask-wavlm-base-plus-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="mazkooleg/digit-mask-wavlm-base-plus-ft") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("mazkooleg/digit-mask-wavlm-base-plus-ft")
model = AutoModelForAudioClassification.from_pretrained("mazkooleg/digit-mask-wavlm-base-plus-ft", device_map="auto")This model is a fine-tuned version of microsoft/wavlm-base-plus 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 |
|---|---|---|---|---|---|
| 0.0091 | 1.0 | 14264 | 0.9991 | 0.9991 | 0.0068 |
| 0.0023 | 2.0 | 28528 | 0.9987 | 0.9987 | 0.0073 |
| 0.0003 | 3.0 | 42792 | 0.9983 | 0.9983 | 0.0101 |