whisper-large-uk
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2527
- eval_wer: 10.0226
- eval_runtime: 9610.7996
- eval_samples_per_second: 0.747
- eval_steps_per_second: 0.023
- epoch: 1.8
- step: 1098
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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Datasets used to train arampacha/whisper-large-uk-2
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Evaluation results
- Wer on Common Voice 11.0test set self-reported10.023
- Wer on Fleurstest set self-reported7.564