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Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the b-brave/speech_disorders_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3733
- Wer: 18.4644
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: 0.001
- train_batch_size: 128
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- training_steps: 64
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
3.0681 | 3.7647 | 16 | 1.7949 | 48.6289 |
0.5772 | 7.5294 | 32 | 0.3912 | 22.3035 |
0.1166 | 11.2941 | 48 | 0.3734 | 18.6472 |
0.0608 | 15.0588 | 64 | 0.3733 | 18.4644 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.2.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for miosipof/asr_michael_medium_v3.2b_augmented
Base model
openai/whisper-medium
Adapter
this model
Dataset used to train miosipof/asr_michael_medium_v3.2b_augmented
Evaluation results
- Wer on b-brave/speech_disorders_voiceself-reported18.464