Whisper_Large_Mongolian
This model is a fine-tuned version of openai/whisper-large. It achieves the following results on the evaluation set:
- eval_loss: 0.3309
- eval_wer: 29.1925
- eval_runtime: 1202.8614
- eval_samples_per_second: 1.539
- eval_steps_per_second: 0.193
- epoch: 5.64
- step: 3000
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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Cafet/whisper-mongolian-version-0.1
Base model
openai/whisper-large