s3prl/superb
Viewer • Updated • 304k • 881 • 33
How to use Jungwoo4021/wav2vec2-base-ks-padpt3200 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Jungwoo4021/wav2vec2-base-ks-padpt3200") # Load model directly
from transformers import AutoProcessor, AutoModelForSequenceClassification
processor = AutoProcessor.from_pretrained("Jungwoo4021/wav2vec2-base-ks-padpt3200")
model = AutoModelForSequenceClassification.from_pretrained("Jungwoo4021/wav2vec2-base-ks-padpt3200", device_map="auto")This model is a fine-tuned version of facebook/wav2vec2-base on the superb 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 | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3802 | 1.0 | 50 | 1.5035 | 0.6121 |
| 1.0153 | 2.0 | 100 | 1.2818 | 0.6200 |
| 0.9105 | 3.0 | 150 | 1.3827 | 0.5380 |
| 0.8535 | 4.0 | 200 | 1.3513 | 0.5587 |
| 0.7982 | 5.0 | 250 | 1.4749 | 0.5068 |
| 0.7754 | 6.0 | 300 | 1.5109 | 0.5025 |
| 0.749 | 7.0 | 350 | 1.6198 | 0.4476 |
| 0.7497 | 8.0 | 400 | 1.5480 | 0.4850 |
| 0.7386 | 9.0 | 450 | 1.6052 | 0.4665 |
| 0.7185 | 10.0 | 500 | 1.6085 | 0.4734 |