Speech Translation Models
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whisper-small-OpenSLR-GL-EN
This model is a fine-tuned version of openai/whisper-small on juanjucm/OpenSLR-SpeechT-GL-EN. It achieves the following results on the evaluation set:
- Loss: 0.7134
- Wer: 37.6147
- Bleu: 50.9676
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.25e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Bleu |
|---|---|---|---|---|---|
| 0.3055 | 1.0 | 150 | 0.6858 | 40.7110 | 47.7920 |
| 0.0378 | 3.0 | 450 | 0.6819 | 38.6959 | 49.8621 |
| 0.013 | 4.0 | 600 | 0.7134 | 37.6147 | 50.9676 |
| 0.014 | 5.0 | 750 | 0.7308 | 38.0570 | 49.2006 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
openai/whisper-small