Downloads · 30 days
9
26% of all-time downloads
yesj1234/xlsr_mid1_zh-ko
xlsr_mid1_zh-ko is a automatic speech recognition model from yesj1234. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
9
26% of all-time downloads
All-time downloads
34
Public
Repo size
8.9 GB
Likes
0
Public
Click a slice to open those files.
.pt5 GB · 57%
From the Hugging Face model README
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the ./SAMPLE_SPEECH.PY - NA 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 | Cer |
|---|---|---|---|---|
| 6.0153 | 0.5 | 330 | 5.3438 | 0.9522 |
| 5.3776 | 1.0 | 660 | 5.1534 | 0.9409 |
| 5.2604 | 1.5 | 990 | 5.0832 | 0.9108 |
| 5.2393 | 2.01 | 1320 | 5.0655 | 0.9073 |
| 5.1721 | 2.51 | 1650 | 5.0464 | 0.9000 |
| 5.1619 | 3.01 | 1980 | 5.0244 | 0.9045 |
| 5.1308 | 3.51 | 2310 | 5.0216 | 0.9020 |
| 5.0971 | 4.01 | 2640 | 4.9341 | 0.9040 |
| 5.0137 | 4.51 | 2970 | 4.8795 | 0.9144 |
| 4.9341 | 5.02 | 3300 | 4.7250 | 0.9039 |
| 4.6832 | 5.52 | 3630 | 4.2140 | 0.8367 |
| 4.1627 | 6.02 | 3960 | 3.4010 | 0.7318 |
| 3.5448 | 6.52 | 4290 | 2.8830 | 0.6480 |
| 3.2576 | 7.02 | 4620 | 2.6253 | 0.6266 |
| 2.8561 | 7.52 | 4950 | 2.4300 | 0.5866 |
| 2.7894 | 8.02 | 5280 | 2.2998 | 0.5750 |
| 2.6018 | 8.53 | 5610 | 2.1878 | 0.5549 |
| 2.546 | 9.03 | 5940 | 2.1450 | 0.5351 |
| 2.3787 | 9.53 | 6270 | 2.1027 | 0.5340 |
| 2.335 | 10.03 | 6600 | 2.0304 | 0.5166 |
| 2.2138 | 10.53 | 6930 | 2.0100 | 0.5165 |
| 2.2381 | 11.03 | 7260 | 1.9651 | 0.5031 |
| 2.1108 | 11.53 | 7590 | 1.9666 | 0.5035 |
| 2.0916 | 12.04 | 7920 | 1.9136 | 0.4998 |
| 2.0229 | 12.54 | 8250 | 1.8988 | 0.5028 |
| 2.0056 | 13.04 | 8580 | 1.8769 | 0.4996 |
| 1.9245 | 13.54 | 8910 | 1.8716 | 0.4955 |
| 1.9378 | 14.04 | 9240 | 1.8561 | 0.4946 |
| 1.9003 | 14.54 | 9570 | 1.8485 | 0.4936 |