Danieljava/whisper-small-finetuned-asr-random-data-20260304_183211
06
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Whisper Small Multilingual(random(trainedondata) - EN/YO/FR/IG/HA/ES
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7764
- Wer: 0.4243
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- trainbatchsize: 16
- evalbatchsize: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lrschedulertype: constantwithwarmup
- lrschedulerwarmup_steps: 50
- training_steps: 1000
- mixedprecisiontraining: Native AMP
Training results
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2