Speech Translation Models
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whisper-large-v3-turbo-OpenSLR-GL-EN
This model is a fine-tuned version of openai/whisper-large-v3-turbo on juanjucm/OpenSLR-SpeechT-GL-EN. It achieves the following results on the evaluation set:
- Loss: 0.8768
- Wer: 36.7059
- Bleu: 49.4165
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-06
- 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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Bleu |
|---|---|---|---|---|---|
| 0.5639 | 1.0 | 62 | 1.0983 | 41.4588 | 42.0181 |
| 0.2002 | 2.0 | 124 | 0.9388 | 41.6471 | 42.2327 |
| 0.0984 | 3.0 | 186 | 0.8720 | 37.5529 | 46.4185 |
| 0.0289 | 4.0 | 248 | 0.8828 | 38.6353 | 45.8710 |
| 0.028 | 5.0 | 310 | 0.8531 | 40.3294 | 44.8830 |
| 0.0101 | 6.0 | 372 | 0.8768 | 36.7059 | 49.4165 |
| 0.0085 | 7.0 | 434 | 0.9114 | 38.6353 | 47.3759 |
| 0.0059 | 8.0 | 496 | 0.9230 | 38.1176 | 47.2525 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for juanjucm/whisper-large-v3-turbo-OpenSLR-GL-EN
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo