mazkooleg/0-9up_google_speech_commands_augmented_raw
Viewer • Updated • 1.1M • 914
How to use mazkooleg/0-9up-hubert-base-ls960-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="mazkooleg/0-9up-hubert-base-ls960-ft") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("mazkooleg/0-9up-hubert-base-ls960-ft")
model = AutoModelForAudioClassification.from_pretrained("mazkooleg/0-9up-hubert-base-ls960-ft", device_map="auto")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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.1205 | 1.0 | 8558 | 0.9955 | 0.0173 |
| 0.0638 | 2.0 | 17116 | 0.9973 | 0.0123 |
| 0.0747 | 3.0 | 25674 | 0.9964 | 0.0183 |
| 0.0636 | 4.0 | 34232 | 0.9958 | 0.0201 |
| 0.0531 | 5.0 | 42790 | 0.9967 | 0.0168 |