Whisper Medium Catalan
This model is a fine-tuned version of openai/whisper-Medium on the 10 hrs of Catalan Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 4.9217
- eval_wer: 132.1947
- eval_runtime: 3848.0596
- eval_samples_per_second: 0.78
- eval_steps_per_second: 0.78
- epoch: 1.14
- step: 2000
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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2