PolyAI/minds14
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How to use susnato/whisper-tiny-en-minds14 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="susnato/whisper-tiny-en-minds14") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("susnato/whisper-tiny-en-minds14")
model = AutoModelForSpeechSeq2Seq.from_pretrained("susnato/whisper-tiny-en-minds14")This model is a fine-tuned version of openai/whisper-tiny on the Minds 14 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 Ortho | Wer |
|---|---|---|---|---|---|
| 3.7423 | 1.0 | 15 | 2.9584 | 0.5275 | 0.4079 |
| 0.5112 | 2.0 | 30 | 0.7722 | 0.4022 | 0.3731 |
| 0.2542 | 3.0 | 45 | 0.6002 | 0.3837 | 0.3619 |
| 0.1196 | 4.0 | 60 | 0.5739 | 0.3492 | 0.3294 |
| 0.0214 | 5.0 | 75 | 0.5843 | 0.3652 | 0.3542 |
| 0.0659 | 6.0 | 90 | 0.6047 | 0.3418 | 0.3282 |
| 0.0322 | 7.0 | 105 | 0.6134 | 0.3560 | 0.3424 |
| 0.0049 | 8.0 | 120 | 0.6180 | 0.3553 | 0.3406 |
| 0.0348 | 9.0 | 135 | 0.6242 | 0.3442 | 0.3323 |
| 0.1332 | 10.0 | 150 | 0.6262 | 0.3455 | 0.3335 |