Whisper Small MS - FLEURS
This model is a fine-tuned version of openai/whisper-small on the FLEURS dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3324
- eval_wer: 15.6453
- eval_runtime: 347.6066
- eval_samples_per_second: 2.155
- eval_steps_per_second: 0.27
- epoch: 10.75
- step: 1000
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
- Downloads last month
- 6