Whisper Base Ukrainian
This model is a fine-tuned version of arun100/whisper-base-uk-1 on the google/fleurs uk_ua dataset. It achieves the following results on the evaluation set:
- Loss: 0.4710
- Wer: 33.5630
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: 2.5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2683 | 95.0 | 1000 | 0.4710 | 33.5630 |
0.142 | 190.0 | 2000 | 0.4714 | 33.8344 |
0.0871 | 285.0 | 3000 | 0.4782 | 33.9596 |
0.0656 | 380.0 | 4000 | 0.4830 | 33.7230 |
0.0595 | 476.0 | 5000 | 0.4847 | 33.7161 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
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Dataset used to train arun100/whisper-base-uk-2
Evaluation results
- Wer on google/fleurs uk_uatest set self-reported33.563