Prajwal-143/ASR-Tamil-cleaned
Viewer • Updated • 312k • 970 • 2
How to use Logii33/whisper-large-v3-ta with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Logii33/whisper-large-v3-ta") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Logii33/whisper-large-v3-ta")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Logii33/whisper-large-v3-ta")This model is a fine-tuned version of openai/whisper-large-v3 on the asr-tamil-cleaned 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 | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1482 | 0.0143 | 500 | 0.1601 | 99.7086 | 192.4581 |
Base model
openai/whisper-large-v3