Whisper finetuned for ceb
This model is a fine-tuned version of openai/whisper-tiny on the Fleurs Ceb subset dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6132
- eval_wer: 40.1716
- eval_runtime: 321.4179
- eval_samples_per_second: 1.683
- eval_steps_per_second: 0.212
- epoch: 0.14
- step: 30
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: reduce_lr_on_plateau
- training_steps: 1000
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0