AILAB-VNUHCM/vivos
Updated • 546 • 16
How to use KieuTruongz/working with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="KieuTruongz/working") # Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("KieuTruongz/working")
model = AutoModelForCTC.from_pretrained("KieuTruongz/working")This model is a fine-tuned version of facebook/wav2vec2-base on the vivos 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 | Wer |
|---|---|---|---|---|
| 5.8286 | 1.0274 | 300 | 3.6649 | 1.0 |
| 3.3501 | 2.0548 | 600 | 2.5006 | 0.9971 |
| 1.0597 | 3.0822 | 900 | 0.5530 | 0.3923 |
| 0.5399 | 4.1096 | 1200 | 0.4242 | 0.3123 |
| 0.4275 | 5.1370 | 1500 | 0.3533 | 0.2677 |
| 0.363 | 6.1644 | 1800 | 0.3392 | 0.2368 |
| 0.3145 | 7.1918 | 2100 | 0.3485 | 0.2331 |
| 0.2803 | 8.2192 | 2400 | 0.3139 | 0.2136 |
| 0.2551 | 9.2466 | 2700 | 0.2939 | 0.2065 |
Base model
facebook/wav2vec2-base