VRCLC Malayalam ASR : Models
Collection
6 items
•
Updated
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an these datasets: IMASC, MSC, OpenSLR Malayalam Train split, Festvox Malayalam, common_voice_16_1 It achieves the following results on the evaluation set:
Trained on NVIDIA A100 GPU
The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.1416 | 0.46 | 600 | 0.3393 | 0.4616 |
0.1734 | 0.92 | 1200 | 0.2414 | 0.3493 |
0.1254 | 1.38 | 1800 | 0.2205 | 0.2963 |
0.1097 | 1.84 | 2400 | 0.2157 | 0.3133 |
0.0923 | 2.3 | 3000 | 0.1854 | 0.2473 |
0.0792 | 2.76 | 3600 | 0.1939 | 0.2471 |
0.0696 | 3.22 | 4200 | 0.1720 | 0.2282 |
0.0589 | 3.68 | 4800 | 0.1768 | 0.2013 |
0.0552 | 4.14 | 5400 | 0.1635 | 0.1864 |
0.0437 | 4.6 | 6000 | 0.1501 | 0.1826 |
0.0408 | 5.06 | 6600 | 0.1500 | 0.1645 |
0.0314 | 5.52 | 7200 | 0.1559 | 0.1655 |
0.0317 | 5.98 | 7800 | 0.1448 | 0.1553 |
0.022 | 6.44 | 8400 | 0.1592 | 0.1590 |
0.0218 | 6.9 | 9000 | 0.1431 | 0.1458 |
0.0154 | 7.36 | 9600 | 0.1514 | 0.1366 |
0.0141 | 7.82 | 10200 | 0.1540 | 0.1383 |
0.0113 | 8.28 | 10800 | 0.1558 | 0.1391 |
0.0085 | 8.74 | 11400 | 0.1612 | 0.1356 |
0.0072 | 9.2 | 12000 | 0.1697 | 0.1289 |
0.0046 | 9.66 | 12600 | 0.1722 | 0.1299 |
Base model
facebook/w2v-bert-2.0