Whisper Small CPU Finetuned
This model is a fine-tuned version of openai/whisper-small on the LibriSpeech ASR Dummy dataset. It achieves the following results on the evaluation set:
- Loss: 0.8936
- Wer: 0.0
Model description
More information needed
Intended uses & limitations
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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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8939 | 0.5 | 5 | 0.9602 | 0.0 |
| 0.7066 | 1.0 | 10 | 0.8936 | 0.0 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cpu
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
openai/whisper-small