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 1000, epoch 2.54, and it achieves the following results on the evaluation set:
- Loss: 1.9005
- Bleu: 21.83
- Chrf: 37.13
- Wer: 80.4593
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Experiment
- Data (v1.1: IWSLT2023-GA-EN; v1.2: +FLEURS-GA-EN)
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: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer |
|---|---|---|---|---|---|---|
| 2.6826 | 0.25 | 100 | 2.0993 | 7.23 | 22.29 | 100.7654 |
| 2.1287 | 0.51 | 200 | 1.9451 | 9.37 | 27.74 | 125.9343 |
| 1.8482 | 0.76 | 300 | 1.8356 | 13.11 | 30.65 | 103.5570 |
| 1.2977 | 1.02 | 400 | 1.8643 | 10.56 | 30.86 | 128.5907 |
| 0.8068 | 1.27 | 500 | 1.8658 | 18.23 | 35.17 | 82.6204 |
| 0.7257 | 1.52 | 600 | 1.8493 | 17.81 | 34.13 | 90.7249 |
| 0.6202 | 1.78 | 700 | 1.8312 | 17.6 | 35.19 | 92.2107 |
| 0.4348 | 2.03 | 800 | 1.8771 | 17.9 | 35.66 | 91.9856 |
| 0.2566 | 2.28 | 900 | 1.9088 | 20.14 | 36.79 | 81.4498 |
| 0.2301 | 2.54 | 1000 | 1.9005 | 21.83 | 37.13 | 80.4593 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2