whisper-small-ko-E30_Yfreq
This model is a fine-tuned version of openai/whisper-small on the aihub elder over 70 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1811
- Cer: 5.4335
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
0.3481 | 0.13 | 100 | 0.2725 | 7.0019 |
0.2173 | 0.26 | 200 | 0.2210 | 6.0679 |
0.184 | 0.39 | 300 | 0.2115 | 5.8388 |
0.1949 | 0.52 | 400 | 0.2045 | 5.6685 |
0.2008 | 0.64 | 500 | 0.2024 | 6.4850 |
0.1712 | 0.77 | 600 | 0.1937 | 6.1854 |
0.1504 | 0.9 | 700 | 0.1948 | 5.5569 |
0.0714 | 1.03 | 800 | 0.1867 | 5.1809 |
0.0706 | 1.16 | 900 | 0.1894 | 5.5216 |
0.0784 | 1.29 | 1000 | 0.1904 | 5.3102 |
0.0766 | 1.42 | 1100 | 0.1889 | 5.8094 |
0.0663 | 1.55 | 1200 | 0.1835 | 5.7448 |
0.0751 | 1.68 | 1300 | 0.1815 | 5.3219 |
0.0585 | 1.81 | 1400 | 0.1808 | 5.2044 |
0.0728 | 1.93 | 1500 | 0.1811 | 5.4335 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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