Whisper small Ar - AxAI
This model is a fine-tuned version of openai/whisper-small on the Client dataset. It achieves the following results on the evaluation set:
- Loss: 1.5990
- Wer: 84.1146
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8044 | 6.37 | 200 | 1.2417 | 69.9219 |
| 0.036 | 12.75 | 400 | 1.1791 | 60.9375 |
| 0.0108 | 19.12 | 600 | 1.3128 | 80.2083 |
| 0.0035 | 25.5 | 800 | 1.3641 | 62.6953 |
| 0.0009 | 31.87 | 1000 | 1.4066 | 66.6016 |
| 0.0004 | 38.25 | 1200 | 1.4410 | 64.5833 |
| 0.0003 | 44.62 | 1400 | 1.4712 | 63.3464 |
| 0.0002 | 51.0 | 1600 | 1.4927 | 63.6068 |
| 0.0002 | 57.37 | 1800 | 1.5102 | 67.1875 |
| 0.0002 | 63.75 | 2000 | 1.5254 | 66.6016 |
| 0.0001 | 70.12 | 2200 | 1.5393 | 77.8646 |
| 0.0001 | 76.49 | 2400 | 1.5512 | 77.9297 |
| 0.0001 | 82.87 | 2600 | 1.5616 | 77.7344 |
| 0.0001 | 89.24 | 2800 | 1.5710 | 83.1380 |
| 0.0001 | 95.62 | 3000 | 1.5791 | 88.0859 |
| 0.0001 | 101.99 | 3200 | 1.5854 | 88.1510 |
| 0.0001 | 108.37 | 3400 | 1.5910 | 88.0859 |
| 0.0001 | 114.74 | 3600 | 1.5953 | 84.1146 |
| 0.0001 | 121.12 | 3800 | 1.5978 | 84.1797 |
| 0.0001 | 127.49 | 4000 | 1.5990 | 84.1146 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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