Whisper Small Five 20K - Chee Li
This model is a fine-tuned version of openai/whisper-base on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5771
- Wer: 22.0375
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2500
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4014 | 1.0560 | 1000 | 0.4369 | 25.7071 |
0.2677 | 2.1119 | 2000 | 0.3905 | 22.1327 |
0.1651 | 3.1679 | 3000 | 0.3856 | 21.2139 |
0.1102 | 4.2239 | 4000 | 0.3920 | 20.4471 |
0.0514 | 5.2798 | 5000 | 0.4072 | 21.2883 |
0.0255 | 6.3358 | 6000 | 0.4273 | 21.4687 |
0.0184 | 7.3918 | 7000 | 0.4442 | 21.6251 |
0.01 | 8.4477 | 8000 | 0.4635 | 21.3397 |
0.0051 | 9.5037 | 9000 | 0.4805 | 21.3867 |
0.0043 | 10.5597 | 10000 | 0.4924 | 21.5508 |
0.0025 | 11.6156 | 11000 | 0.5054 | 21.5847 |
0.0023 | 12.6716 | 12000 | 0.5166 | 22.0703 |
0.0016 | 13.7276 | 13000 | 0.5292 | 21.7509 |
0.0012 | 14.7835 | 14000 | 0.5375 | 21.7925 |
0.001 | 15.8395 | 15000 | 0.5480 | 21.9325 |
0.0008 | 16.8955 | 16000 | 0.5565 | 21.8866 |
0.0008 | 17.9514 | 17000 | 0.5638 | 21.9423 |
0.0005 | 19.0074 | 18000 | 0.5709 | 21.9916 |
0.0005 | 20.0634 | 19000 | 0.5755 | 22.0397 |
0.0004 | 21.1193 | 20000 | 0.5771 | 22.0375 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for CheeLi03/whisper-5b-20k
Base model
openai/whisper-base