s3prl/superb
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How to use Jungwoo4021/wav2vec2-base-ks-finetuning with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="Jungwoo4021/wav2vec2-base-ks-finetuning") # Load model directly
from transformers import AutoProcessor, AutoModelForSequenceClassification
processor = AutoProcessor.from_pretrained("Jungwoo4021/wav2vec2-base-ks-finetuning")
model = AutoModelForSequenceClassification.from_pretrained("Jungwoo4021/wav2vec2-base-ks-finetuning")This model is a fine-tuned version of facebook/wav2vec2-base on the superb 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 |
|---|---|---|---|---|
| 1.6773 | 1.0 | 50 | 1.6218 | 0.6209 |
| 1.4707 | 2.0 | 100 | 1.4400 | 0.6209 |
| 1.1387 | 3.0 | 150 | 1.0470 | 0.6599 |
| 0.7909 | 4.0 | 200 | 0.6997 | 0.8903 |
| 0.5488 | 5.0 | 250 | 0.4567 | 0.9640 |
| 0.4195 | 6.0 | 300 | 0.3288 | 0.9754 |
| 0.3445 | 7.0 | 350 | 0.2598 | 0.9809 |
| 0.3107 | 8.0 | 400 | 0.2261 | 0.9813 |
| 0.2781 | 9.0 | 450 | 0.2104 | 0.9810 |
| 0.2729 | 10.0 | 500 | 0.2050 | 0.9813 |