Whisper Small ar -team 1
This model is a fine-tuned version of openai/whisper-medium on the fleurs data dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.1443
- eval_wer: 23.9750
- eval_runtime: 273.8789
- eval_samples_per_second: 1.563
- eval_steps_per_second: 0.197
- step: 0
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-05
- train_batch_size: 8
- 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: 1000
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Downloads last month
- 3
Model tree for nesrine19/whisper_model-ar
Base model
openai/whisper-medium