Nooon/Donate_a_cry
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How to use jstoone/ast-finetuned-audioset-10-10-0.4593-finetuned-cry with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="jstoone/ast-finetuned-audioset-10-10-0.4593-finetuned-cry") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("jstoone/ast-finetuned-audioset-10-10-0.4593-finetuned-cry")
model = AutoModelForAudioClassification.from_pretrained("jstoone/ast-finetuned-audioset-10-10-0.4593-finetuned-cry")This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the DonateACry 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 |
|---|---|---|---|---|
| 1.6297 | 1.0 | 11 | 1.6891 | 0.3636 |
| 1.1137 | 2.0 | 22 | 1.3156 | 0.4545 |
| 0.5047 | 3.0 | 33 | 1.3955 | 0.4545 |
| 0.2062 | 4.0 | 44 | 1.4002 | 0.6364 |
| 0.0613 | 5.0 | 55 | 1.6693 | 0.5455 |
| 0.0142 | 6.0 | 66 | 1.3452 | 0.6364 |
| 0.0053 | 7.0 | 77 | 1.6914 | 0.5455 |
| 0.0038 | 8.0 | 88 | 1.6689 | 0.5455 |
| 0.0027 | 9.0 | 99 | 1.6357 | 0.5455 |
| 0.002 | 10.0 | 110 | 1.6404 | 0.5455 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593