Speech Translation Models
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whisper-large-v3-turbo-FLEURS-GL-EN
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4958
- Wer: 71.6814
- Bleu: 18.9665
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Bleu |
|---|---|---|---|---|---|
| 4.2751 | 1.0 | 5 | 3.8850 | 76.6962 | 18.0512 |
| 2.3984 | 2.0 | 10 | 2.6965 | 97.0501 | 13.5327 |
| 1.4958 | 3.0 | 15 | 2.2308 | 71.6814 | 18.9665 |
| 1.27 | 4.0 | 20 | 2.0454 | 128.3186 | 12.2446 |
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-FLEURS-GL-EN
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo