Whisper Diin - Part 3
This model is a fine-tuned version of mlouala/whisper-diin-v2 on the Emilia-Dataset dataset.
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
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.4.0
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for mlouala/whisper-diin-v3
Base model
mlouala/whisper-diin-v2