Whisper Tiny GA-EN Speech Translation
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. The best model (this version) is at checkpoint 700, epoch 5.19, and it achieves the following results on the evaluation set:
- Loss: 2.7090
- Bleu: 17.56
- Chrf: 32.23
- Wer: 90.4998
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Experiment
Data Augmentation (processing)
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer |
|---|---|---|---|---|---|---|
| 0.9302 | 0.74 | 100 | 2.1831 | 8.7 | 24.4 | 114.2729 |
| 0.3304 | 1.48 | 200 | 2.2829 | 11.34 | 28.63 | 115.6686 |
| 0.1095 | 2.22 | 300 | 2.4409 | 11.35 | 29.53 | 117.4696 |
| 0.0781 | 2.96 | 400 | 2.5060 | 12.55 | 29.32 | 110.1306 |
| 0.0506 | 3.7 | 500 | 2.6288 | 16.65 | 31.61 | 91.9856 |
| 0.041 | 4.44 | 600 | 2.6641 | 15.82 | 31.65 | 96.1279 |
| 0.0335 | 5.19 | 700 | 2.7090 | 17.56 | 32.23 | 90.4998 |
| 0.0296 | 5.93 | 800 | 2.7257 | 16.61 | 32.11 | 93.0662 |
| 0.0278 | 6.67 | 900 | 2.7528 | 15.38 | 31.57 | 95.7226 |
| 0.0217 | 7.41 | 1000 | 2.7758 | 15.81 | 32.03 | 96.3980 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2