PolyAI/minds14
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How to use Bunny2308/whisper-tiny-minds14 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Bunny2308/whisper-tiny-minds14") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Bunny2308/whisper-tiny-minds14")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Bunny2308/whisper-tiny-minds14", device_map="auto")This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 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 | Wer Ortho |
|---|---|---|---|---|---|
| 0.1502 | 1.0 | 57 | 0.5102 | 0.3294 | 0.3122 |
| 0.0571 | 2.0 | 114 | 0.5214 | 0.3411 | 0.3282 |
| 0.0563 | 3.0 | 171 | 0.5403 | 0.3467 | 0.3300 |
| 0.0183 | 4.0 | 228 | 0.5591 | 0.3448 | 0.3288 |
| 0.0092 | 5.0 | 285 | 0.5730 | 0.3362 | 0.3202 |
| 0.0031 | 6.0 | 342 | 0.5926 | 0.3325 | 0.3177 |
| 0.0051 | 7.0 | 399 | 0.5965 | 0.3405 | 0.3282 |
| 0.0018 | 8.0 | 456 | 0.6059 | 0.3381 | 0.3257 |
| 0.0023 | 9.0 | 513 | 0.6084 | 0.3387 | 0.3263 |
| 0.0017 | 10.0 | 570 | 0.6098 | 0.3448 | 0.3331 |
Base model
openai/whisper-tiny