whisper-large-v2-finetuning
This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1803
- eval_wer: 14.9238
- eval_runtime: 3860.013
- eval_samples_per_second: 2.453
- eval_steps_per_second: 0.307
- epoch: 1.5267
- 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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