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whisper-large-ti
This model is a fine-tuned version of openai/whisper-large on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- eval_loss: 2.2921
- eval_wer: 127.2727
- eval_runtime: 18.034
- eval_samples_per_second: 0.222
- eval_steps_per_second: 0.055
- epoch: 200.0
- step: 200
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 200
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.2
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