DOLMA ASR Models
Collection
Models trained on very low-resource Middle Eastern languages
•
9 items
•
Updated
This model is a fine-tuned version of openai/whisper-small on the None 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 | Mazanderani Wer | Mazanderani Cer | Gilaki Wer | Gilaki Cer | Zazaki Wer | Zazaki Cer | Laki Kurdish Wer | Laki Kurdish Cer | Talysh Wer | Talysh Cer | Hawrami Wer | Hawrami Cer | Southern Kurdish Wer | Southern Kurdish Cer | Avg Wer | Avg Cer |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.6946 | 1.0 | 82 | 0.7662 | 0.8120 | 0.3224 | 0.9556 | 0.3751 | 1.0270 | 1.0389 | 0.7939 | 0.2733 | 0.9167 | 0.3333 | 0.5246 | 0.1155 | 0.6801 | 0.2192 | 0.8157 | 0.3825 |
0.3864 | 2.0 | 164 | 0.5172 | 0.6093 | 0.1846 | 0.9579 | 0.3454 | 0.7451 | 0.2813 | 0.5644 | 0.1547 | 1.0 | 0.5 | 0.3806 | 0.0773 | 0.5484 | 0.1743 | 0.6865 | 0.2454 |
0.3234 | 3.0 | 246 | 0.4686 | 0.5476 | 0.1652 | 0.9633 | 0.3514 | 0.6740 | 0.2363 | 0.5231 | 0.1362 | 1.0 | 0.5 | 0.3533 | 0.0722 | 0.4936 | 0.1674 | 0.6507 | 0.2327 |
0.2786 | 4.0 | 328 | 0.4527 | 0.5278 | 0.1596 | 0.9083 | 0.3179 | 0.6422 | 0.2133 | 0.5047 | 0.1334 | 1.0 | 0.5 | 0.3485 | 0.0732 | 0.4948 | 0.1769 | 0.6323 | 0.2249 |
0.2586 | 5.0 | 410 | 0.4509 | 0.5278 | 0.1615 | 0.9176 | 0.3175 | 0.6324 | 0.2020 | 0.4904 | 0.1247 | 1.0 | 0.5 | 0.3459 | 0.0708 | 0.4930 | 0.1718 | 0.6296 | 0.2212 |
Base model
openai/whisper-small