s3prl/superb
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How to use artyomboyko/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="artyomboyko/wav2vec2-base-finetuned-ks") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("artyomboyko/wav2vec2-base-finetuned-ks")
model = AutoModelForAudioClassification.from_pretrained("artyomboyko/wav2vec2-base-finetuned-ks")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 | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.4397 | 1.0 | 798 | 0.2810 | 0.9651 | 0.9289 | 0.9361 |
| 0.2067 | 2.0 | 1597 | 0.1142 | 0.9769 | 0.9536 | 0.9593 |
| 0.1881 | 3.0 | 2395 | 0.0829 | 0.9821 | 0.9644 | 0.9693 |
| 0.1167 | 4.0 | 3194 | 0.0752 | 0.9831 | 0.9644 | 0.9726 |
| 0.13 | 5.0 | 3990 | 0.0711 | 0.9832 | 0.9664 | 0.9720 |
Base model
facebook/wav2vec2-base