Whisper Base GA-EN Speech Translation
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. The best model (this version) is at checkpoint 1800, epoch 1.94, and it achieves the following results on the evaluation set:
- Loss: 1.6780
- Bleu: 22.52
- Chrf: 39.24
- Wer: 76.7222
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
---|---|---|---|---|---|---|
2.4277 | 0.11 | 100 | 4.21 | 19.8 | 2.2931 | 144.9797 |
2.1912 | 0.22 | 200 | 6.79 | 22.82 | 2.0213 | 152.5439 |
1.9199 | 0.32 | 300 | 6.62 | 24.85 | 1.9041 | 180.0090 |
1.7525 | 0.43 | 400 | 13.14 | 30.42 | 1.8026 | 98.1090 |
1.6623 | 0.54 | 500 | 17.73 | 34.37 | 1.7467 | 90.5448 |
1.4937 | 0.65 | 600 | 16.85 | 33.97 | 1.7301 | 92.3458 |
1.3587 | 0.76 | 700 | 14.77 | 33.3 | 1.6499 | 101.7109 |
1.274 | 0.86 | 800 | 18.28 | 35.46 | 1.6641 | 89.1941 |
1.1514 | 0.97 | 900 | 21.17 | 37.05 | 1.6172 | 80.1441 |
0.6932 | 1.08 | 1000 | 16.81 | 35.35 | 1.6421 | 99.0095 |
0.8294 | 1.19 | 1100 | 1.6699 | 18.49 | 36.78 | 90.9500 |
0.7662 | 1.29 | 1200 | 1.7147 | 17.15 | 34.75 | 95.8577 |
0.7704 | 1.4 | 1300 | 1.6752 | 15.65 | 35.08 | 104.2774 |
0.7333 | 1.51 | 1400 | 1.6812 | 19.17 | 36.87 | 89.2841 |
0.6879 | 1.62 | 1500 | 1.6719 | 19.09 | 37.98 | 84.6015 |
0.6297 | 1.73 | 1600 | 1.6847 | 19.43 | 37.28 | 89.5092 |
0.5843 | 1.83 | 1700 | 1.6659 | 17.74 | 38.08 | 98.1990 |
0.5342 | 1.94 | 1800 | 1.6780 | 22.52 | 39.24 | 76.7222 |
0.2743 | 2.05 | 1900 | 1.7151 | 22.48 | 39.05 | 78.8834 |
0.2932 | 2.16 | 2000 | 1.7044 | 17.65 | 38.01 | 99.2796 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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