whisper-tiny-fo-100h-5k-steps_v2
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4496
- Wer: 71.2805
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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.7688 | 0.2320 | 1000 | 0.7930 | 93.5524 |
0.5536 | 0.4640 | 2000 | 0.5865 | 77.9042 |
0.4716 | 0.6961 | 3000 | 0.5056 | 76.4043 |
0.4447 | 0.9281 | 4000 | 0.4647 | 72.0958 |
0.3585 | 1.1601 | 5000 | 0.4496 | 71.2805 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny