whisper-large-v3-bem
This model is a fine-tuned version of openai/whisper-large-v3 on the BembaSpeech bem dataset. It achieves the following results on the evaluation set:
- Loss: 0.3448
- Wer: 0.3758
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: 1.75e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4685 | 1.0084 | 500 | 0.3448 | 0.3758 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for csikasote/whisper-large-v3-bem
Base model
openai/whisper-large-v3Space using csikasote/whisper-large-v3-bem 1
Evaluation results
- Wer on BembaSpeech bemself-reported0.376
- WER on bembaspeechtest set self-reported37.960
- WER on BembaSpeechtest set self-reported37.960
- WER on BembaSpeechtest set self-reported41.890