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ctaguchi/ssc-aln-model
ssc-aln-model is a automatic speech recognition model from ctaguchi. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model was trained from scratch 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 | Cer | Wer |
|---|---|---|---|---|---|
| 2.6542 | 0.1027 | 100 | 2.7873 | 0.9127 | 1.0 |
| 2.7312 | 0.2054 | 200 | 2.6739 | 0.8102 | 0.9999 |
| 2.7166 | 0.3082 | 300 | 2.3973 | 0.8100 | 0.9998 |
| 2.6442 | 0.4109 | 400 | 2.5701 | 0.7773 | 0.9863 |
| 2.6282 | 0.5136 | 500 | 2.4967 | 0.7596 | 1.0 |
| 2.6793 | 0.6163 | 600 | 2.4465 | 0.8274 | 0.9988 |
| 2.5982 | 0.7191 | 700 | 2.4531 | 0.7070 | 0.9893 |
| 2.5929 | 0.8218 | 800 | 2.3973 | 0.7647 | 0.9991 |
| 2.6211 | 0.9245 | 900 | 2.3430 | 0.7394 | 0.9911 |
| 2.5614 | 1.0267 | 1000 | 2.2116 | 0.6708 | 0.9887 |
| 2.5421 | 1.1294 | 1100 | 2.1762 | 0.7062 | 0.9970 |
| 2.5272 | 1.2322 | 1200 | 2.1483 | 0.6747 | 0.9907 |
| 2.4457 | 1.3349 | 1300 | 2.1416 | 0.6783 | 0.9754 |
| 2.4582 | 1.4376 | 1400 | 2.1515 | 0.6323 | 0.9812 |
| 2.5182 | 1.5403 | 1500 | 2.1518 | 0.6933 | 0.9828 |
| 2.545 | 1.6430 | 1600 | 2.1046 | 0.6844 | 0.9948 |
| 2.4768 | 1.7458 | 1700 | 2.0930 | 0.6794 | 0.9971 |
| 2.437 | 1.8485 | 1800 | 2.0755 | 0.6974 | 0.9977 |
| 2.4652 | 1.9512 | 1900 | 2.0531 | 0.6387 | 0.9852 |
| 2.4666 | 2.0534 | 2000 | 2.0942 | 0.6326 | 0.9725 |
| 2.4098 | 2.1561 | 2100 | 2.1318 | 0.7399 | 0.9999 |
| 2.295 | 2.2589 | 2200 | 2.0930 | 0.6261 | 0.9975 |
| 2.3255 | 2.3616 | 2300 | 2.0553 | 0.6080 | 0.9830 |
| 2.3362 | 2.4643 | 2400 | 2.0664 | 0.6241 | 0.9820 |
| 2.324 | 2.5670 | 2500 | 2.0415 | 0.6090 | 0.9839 |
| 2.3254 | 2.6697 | 2600 | 2.0766 | 0.5845 | 0.9765 |
| 2.3232 | 2.7725 | 2700 | 2.0245 | 0.6318 | 0.9836 |
| 2.2821 | 2.8752 | 2800 | 1.9850 | 0.6249 | 0.9870 |
| 2.2661 | 2.9779 | 2900 | 1.9709 | 0.6247 | 0.9770 |
| 2.2066 | 3.0801 | 3000 | 2.0029 | 0.5864 | 0.9691 |
| 2.1706 | 3.1828 | 3100 | 1.9698 | 0.5725 | 0.9681 |
| 2.1382 | 3.2856 | 3200 | 1.9499 | 0.5990 | 0.9759 |
| 2.2142 | 3.3883 | 3300 | 1.9464 | 0.6189 | 0.9825 |
| 2.2512 | 3.4910 | 3400 | 1.9367 | 0.6020 | 0.9843 |
| 2.1671 | 3.5937 | 3500 | 1.9393 | 0.5939 | 0.9799 |
| 2.2047 | 3.6965 | 3600 | 1.9381 | 0.5728 | 0.9700 |
| 2.1303 | 3.7992 | 3700 | 1.9116 | 0.5683 | 0.9722 |
| 2.1517 | 3.9019 | 3800 | 1.9412 | 0.5383 | 0.9495 |
| 2.2205 | 4.0041 | 3900 | 1.8760 | 0.5827 | 0.9780 |
| 2.07 | 4.1068 | 4000 | 1.9216 | 0.5793 | 0.9768 |
| 2.049 | 4.2096 | 4100 | 1.9057 | 0.5595 | 0.9694 |
| 2.057 | 4.3123 | 4200 | 1.9335 | 0.5549 | 0.9664 |
| 2.0582 | 4.4150 | 4300 | 1.9117 | 0.5552 | 0.9675 |
| 2.0678 | 4.5177 | 4400 | 1.8778 | 0.5699 | 0.9767 |
| 2.0643 | 4.6204 | 4500 | 1.8775 | 0.5704 | 0.9778 |
| 1.9829 | 4.7232 | 4600 | 1.8712 | 0.5704 | 0.9780 |
| 2.0293 | 4.8259 | 4700 | 1.8655 | 0.5577 | 0.9695 |
| 2.0133 | 4.9286 | 4800 | 1.8647 | 0.5679 | 0.9768 |