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workstation_whisper_base_finetune_teacher__babble_noise_mozilla_100_epochs_batch_4
This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3964
- Wer: 36.5051
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0214 | 7.35 | 500 | 0.8448 | 36.1291 |
| 0.3301 | 14.7 | 1000 | 0.9065 | 35.5511 |
| 0.0745 | 22.06 | 1500 | 1.1071 | 36.1535 |
| 0.0089 | 29.41 | 2000 | 1.2245 | 36.1082 |
| 0.0026 | 36.76 | 2500 | 1.3039 | 36.3171 |
| 0.0015 | 44.12 | 3000 | 1.3551 | 36.4216 |
| 0.001 | 51.47 | 3500 | 1.3964 | 36.5051 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0
