whisper_sft_de_classic

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whisper_sft_de_classic

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.1926
• eval_wer: 67.5274
• eval_runtime: 7643.3489
• eval_samples_per_second: 0.654
• eval_steps_per_second: 0.082
• epoch: 2.56
• step: 16000

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 30000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.28.0.dev0
• Pytorch 2.0.0
• Datasets 2.11.0
• Tokenizers 0.13.3