PolyAI/minds14
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How to use alessio21/minds14-finetuned with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="alessio21/minds14-finetuned") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("alessio21/minds14-finetuned")
model = AutoModelForSpeechSeq2Seq.from_pretrained("alessio21/minds14-finetuned")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 Ortho | Wer |
|---|---|---|---|---|---|
| 4.8952 | 1.0 | 28 | 2.9786 | 0.4097 | 0.5373 |
| 2.0364 | 2.0 | 56 | 0.7791 | 0.3813 | 0.4275 |
| 0.5903 | 3.0 | 84 | 0.5917 | 0.3506 | 0.3917 |
| 0.3271 | 4.0 | 112 | 0.5681 | 0.3129 | 0.3381 |
| 0.2543 | 5.0 | 140 | 0.5713 | 0.3365 | 0.3652 |
| 0.1391 | 6.0 | 168 | 0.5896 | 0.3329 | 0.3621 |
| 0.0846 | 7.0 | 196 | 0.6083 | 0.3388 | 0.3658 |
| 0.0481 | 8.0 | 224 | 0.6209 | 0.3583 | 0.3738 |
| 0.0148 | 9.0 | 252 | 0.6625 | 0.3477 | 0.3689 |
| 0.0087 | 10.0 | 280 | 0.6602 | 0.3412 | 0.3578 |
Base model
openai/whisper-tiny