Whisper Small Ar Dict - Azeemx
This model is a fine-tuned version of openai/whisper-small on the custom dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1676
- eval_wer: 24.3635
- eval_runtime: 322.1148
- eval_samples_per_second: 1.201
- eval_steps_per_second: 0.152
- epoch: 4.7319
- step: 3000
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 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
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for WajeehAzeemX/whisper-small-ar-letters
Base model
openai/whisper-small