Finetuned Whisper small darija translate
This model is a fine-tuned version of openai/whisper-small on the Darija-C dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Bleu: 0.7440
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 3.975 | 0.6667 | 10 | 3.4363 | 0.0 |
| 2.1029 | 1.3333 | 20 | 1.5986 | 0.0262 |
| 1.7909 | 2.0 | 30 | 0.9239 | 0.1314 |
| 0.9837 | 2.6667 | 40 | 0.5086 | 0.3289 |
| 0.36 | 3.3333 | 50 | 0.4370 | 0.3911 |
| 0.6361 | 4.0 | 60 | 0.2622 | 0.4561 |
| 0.5227 | 4.6667 | 70 | 0.2506 | 0.5266 |
| 0.3307 | 5.3333 | 80 | 0.1299 | 0.6123 |
| 0.2438 | 6.0 | 90 | 0.1290 | 0.6057 |
| 0.2864 | 6.6667 | 100 | 0.0838 | 0.6623 |
| 0.073 | 7.3333 | 110 | 0.0965 | 0.6494 |
| 0.1924 | 8.0 | 120 | 0.0859 | 0.7237 |
| 0.0086 | 8.6667 | 130 | 0.0235 | 0.7174 |
| 0.003 | 9.3333 | 140 | 0.0335 | 0.7354 |
| 0.054 | 10.0 | 150 | 0.0096 | 0.7367 |
| 0.0008 | 10.6667 | 160 | 0.0190 | 0.7367 |
| 0.0002 | 11.3333 | 170 | 0.0003 | 0.7440 |
| 0.0001 | 12.0 | 180 | 0.0001 | 0.7440 |
| 0.0002 | 12.6667 | 190 | 0.0001 | 0.7440 |
| 0.0 | 13.3333 | 200 | 0.0000 | 0.7440 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3