Benchmark
Collection
Benchmark
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18 items
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Updated
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1
This model is a fine-tuned version of openai/whisper-small on the superb 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 | Accuracy |
---|---|---|---|---|
0.3599 | 1.0 | 1597 | 0.1546 | 0.9707 |
0.0819 | 2.0 | 3194 | 0.0998 | 0.9762 |
0.0635 | 3.0 | 4791 | 0.1049 | 0.9800 |
0.0437 | 4.0 | 6388 | 0.0905 | 0.9797 |
0.0411 | 5.0 | 7985 | 0.0898 | 0.9809 |
0.0283 | 6.0 | 9582 | 0.1006 | 0.9812 |
0.0229 | 7.0 | 11179 | 0.0976 | 0.9848 |
0.0186 | 8.0 | 12776 | 0.1143 | 0.9825 |
0.0094 | 9.0 | 14373 | 0.1136 | 0.9835 |
0.0066 | 10.0 | 15970 | 0.1172 | 0.9834 |
Base model
openai/whisper-small