Whisper Base Hi - Full fine tuned
This model is a fine-tuned version of openai/whisper-base on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5202
- Wer: 46.0226
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: 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
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2093 | 2.3641 | 1000 | 0.4135 | 48.6273 |
0.0898 | 4.7281 | 2000 | 0.4273 | 45.7038 |
0.0279 | 7.0922 | 3000 | 0.4794 | 45.6334 |
0.0166 | 9.4563 | 4000 | 0.5202 | 46.0226 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
openai/whisper-base