marsyas/gtzan
Updated • 6.61k • 17
How to use nithiroj/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="nithiroj/wav2vec2-base-finetuned-gtzan") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("nithiroj/wav2vec2-base-finetuned-gtzan")
model = AutoModelForAudioClassification.from_pretrained("nithiroj/wav2vec2-base-finetuned-gtzan", device_map="auto")This model is a fine-tuned version of facebook/wav2vec2-base 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 | Accuracy |
|---|---|---|---|---|
| 1.9578 | 1.0 | 113 | 1.8537 | 0.28 |
| 1.4644 | 2.0 | 226 | 1.5867 | 0.5 |
| 0.9624 | 3.0 | 339 | 1.1706 | 0.66 |
| 0.8329 | 4.0 | 452 | 0.8807 | 0.76 |
| 0.5047 | 5.0 | 565 | 0.9421 | 0.73 |
| 0.4525 | 6.0 | 678 | 0.7879 | 0.73 |
| 0.5111 | 7.0 | 791 | 0.6493 | 0.79 |
| 0.1836 | 8.0 | 904 | 0.5938 | 0.85 |
| 0.1806 | 9.0 | 1017 | 0.5787 | 0.84 |
| 0.1338 | 10.0 | 1130 | 0.6608 | 0.81 |
Base model
facebook/wav2vec2-base