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sqrk/COPAS-whisper-lg-3-Nov29
COPAS-whisper-lg-3-Nov29 is a machine learning model from sqrk. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown 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 |
|---|---|---|---|---|
| 0.9253 | 2.3529 | 100 | 0.3717 | 26.4368 |
| 0.1676 | 4.7059 | 200 | 0.2410 | 21.4559 |
| 0.04 | 7.0588 | 300 | 0.2064 | 17.6245 |
| 0.0204 | 9.4118 | 400 | 0.1890 | 18.1171 |
| 0.0092 | 11.7647 | 500 | 0.1929 | 17.8982 |
| 0.0051 | 14.1176 | 600 | 0.1794 | 21.3465 |
| 0.0062 | 16.4706 | 700 | 0.1682 | 14.8331 |
| 0.0046 | 18.8235 | 800 | 0.1798 | 15.2709 |
| 0.0026 | 21.1765 | 900 | 0.1717 | 15.3257 |
| 0.0022 | 23.5294 | 1000 | 0.1805 | 14.7236 |
| 0.0019 | 25.8824 | 1100 | 0.1961 | 15.4351 |
| 0.0027 | 28.2353 | 1200 | 0.1614 | 22.1128 |
| 0.0024 | 30.5882 | 1300 | 0.1653 | 17.4603 |
| 0.0023 | 32.9412 | 1400 | 0.1850 | 17.6793 |
| 0.0023 | 35.2941 | 1500 | 0.1564 | 13.1910 |
| 0.0014 | 37.6471 | 1600 | 0.1551 | 13.8478 |
| 0.002 | 40.0 | 1700 | 0.1533 | 13.5194 |
| 0.0013 | 42.3529 | 1800 | 0.1496 | 13.4100 |
| 0.0007 | 44.7059 | 1900 | 0.1555 | 13.4100 |
| 0.0006 | 47.0588 | 2000 | 0.1524 | 13.3005 |
| 0.0001 | 49.4118 | 2100 | 0.1526 | 13.4647 |
| 0.0001 | 51.7647 | 2200 | 0.1540 | 13.3005 |
| 0.0001 | 54.1176 | 2300 | 0.1549 | 13.2458 |
| 0.0001 | 56.4706 | 2400 | 0.1555 | 13.2458 |
| 0.0001 | 58.8235 | 2500 | 0.1561 | 13.3552 |
| 0.0001 | 61.1765 | 2600 | 0.1565 | 13.3005 |
| 0.0 | 63.5294 | 2700 | 0.1569 | 13.2458 |
| 0.0 | 65.8824 | 2800 | 0.1573 | 13.1910 |
| 0.0 | 68.2353 | 2900 | 0.1576 | 13.1910 |
| 0.0 | 70.5882 | 3000 | 0.1579 | 13.1910 |
| 0.0 | 72.9412 | 3100 | 0.1581 | 13.3552 |
| 0.0 | 75.2941 | 3200 | 0.1584 | 13.4100 |
| 0.0 | 77.6471 | 3300 | 0.1586 | 13.4100 |
| 0.0 | 80.0 | 3400 | 0.1588 | 12.7531 |
| 0.0 | 82.3529 | 3500 | 0.1589 | 13.0816 |
| 0.0 | 84.7059 | 3600 | 0.1591 | 12.6984 |
| 0.0 | 87.0588 | 3700 | 0.1593 | 13.1363 |
| 0.0 | 89.4118 | 3800 | 0.1594 | 13.1363 |
| 0.0 | 91.7647 | 3900 | 0.1594 | 13.0816 |
| 0.0 | 94.1176 | 4000 | 0.1595 | 13.0816 |
| 0.0 | 96.4706 | 4100 | 0.1596 | 13.0816 |
| 0.0 | 98.8235 | 4200 | 0.1596 | 13.1363 |