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bigmorning/whisper_input_decoder_shift_r_labels_with_force__0010
whisper_input_decoder_shift_r_labels_with_force__0010 is a automatic speech recognition model from bigmorning. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of openai/whisper-tiny 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:
| Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch |
|---|---|---|---|---|---|---|
| 5.6249 | 0.0091 | 1.7162 | 4.2965 | 0.0094 | 0.9447 | 0 |
| 4.9223 | 0.0099 | 0.9041 | 4.1562 | 0.0097 | 0.9327 | 1 |
| 4.6814 | 0.0107 | 0.8376 | 3.9245 | 0.0103 | 0.8927 | 2 |
| 4.4407 | 0.0114 | 0.8311 | 3.7252 | 0.0107 | 0.8775 | 3 |
| 4.2445 | 0.0119 | 0.8228 | 3.6283 | 0.0108 | 0.8695 | 4 |
| 4.0889 | 0.0123 | 0.8067 | 3.5310 | 0.0110 | 0.8916 | 5 |
| 3.9575 | 0.0127 | 0.7908 | 3.4478 | 0.0113 | 0.8407 | 6 |
| 3.8547 | 0.0130 | 0.7781 | 3.4227 | 0.0113 | 0.8670 | 7 |
| 3.7599 | 0.0133 | 0.7654 | 3.3519 | 0.0115 | 0.8375 | 8 |
| 3.6763 | 0.0136 | 0.7543 | 3.3183 | 0.0116 | 0.8678 | 9 |