marsyas/gtzan
Updated • 1.71k • 17
How to use TrVuKhah/results with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="TrVuKhah/results") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("TrVuKhah/results")
model = AutoModelForAudioClassification.from_pretrained("TrVuKhah/results")This model is a fine-tuned version of MariaK/distilhubert-finetuned-gtzan-v2 on the GTZAN 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 |
|---|---|---|---|
| 0.0042 | 1.0 | 100 | 0.2518 |
| 0.0021 | 2.0 | 200 | 0.2875 |
| 0.0013 | 3.0 | 300 | 0.2987 |
| 0.0009 | 4.0 | 400 | 0.3040 |
| 0.0007 | 5.0 | 500 | 0.3037 |
| 0.0007 | 6.0 | 600 | 0.3100 |
| 0.0005 | 7.0 | 700 | 0.3114 |
| 0.0005 | 8.0 | 800 | 0.3095 |
| 0.0005 | 9.0 | 900 | 0.3147 |
| 0.0005 | 10.0 | 1000 | 0.3159 |
Base model
MariaK/distilhubert-finetuned-gtzan-v2