Bemba
Collection
Experimental automatic speech recognition models developed for the Bemba language
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32 items
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Updated
This model is a fine-tuned version of openai/whisper-small on the BEMBA dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
0.9127 | 1.0 | 5143 | 0.5881 | 0.4483 | 0.1252 |
0.5091 | 2.0 | 10286 | 0.4981 | 0.3918 | 0.1136 |
0.4171 | 3.0 | 15429 | 0.4668 | 0.3636 | 0.1024 |
0.3332 | 4.0 | 20572 | 0.4638 | 0.3551 | 0.1022 |
0.251 | 5.0 | 25715 | 0.4828 | 0.3585 | 0.1101 |
0.1689 | 6.0 | 30858 | 0.5249 | 0.3631 | 0.1102 |
0.0992 | 7.0 | 36001 | 0.5907 | 0.3645 | 0.1078 |
0.0548 | 8.0 | 41144 | 0.6471 | 0.3676 | 0.1082 |
0.034 | 9.0 | 46287 | 0.7023 | 0.3646 | 0.1071 |
0.0252 | 10.0 | 51430 | 0.7307 | 0.3707 | 0.1129 |
0.0207 | 11.0 | 56573 | 0.7652 | 0.3652 | 0.1071 |
0.0178 | 12.0 | 61716 | 0.7873 | 0.3653 | 0.1088 |
0.0161 | 13.0 | 66859 | 0.8036 | 0.3643 | 0.1093 |
0.0144 | 14.0 | 72002 | 0.8223 | 0.3573 | 0.1064 |
Base model
openai/whisper-small