whisper-small-ko-Yfreq2
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: 0.2663
- Cer: 7.4894
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 |
---|---|---|---|---|
0.257 | 0.13 | 100 | 0.2981 | 8.0005 |
0.1533 | 0.26 | 200 | 0.2729 | 7.5717 |
0.1179 | 0.39 | 300 | 0.2774 | 8.0005 |
0.1285 | 0.52 | 400 | 0.2664 | 7.3661 |
0.1048 | 0.64 | 500 | 0.2702 | 7.4248 |
0.101 | 0.77 | 600 | 0.2702 | 7.1135 |
0.1053 | 0.9 | 700 | 0.2655 | 7.0606 |
0.0405 | 1.03 | 800 | 0.2609 | 6.9901 |
0.031 | 1.16 | 900 | 0.2629 | 6.5378 |
0.0416 | 1.29 | 1000 | 0.2647 | 7.7949 |
0.0356 | 1.42 | 1100 | 0.2693 | 7.6539 |
0.0407 | 1.55 | 1200 | 0.2656 | 6.8374 |
0.0331 | 1.68 | 1300 | 0.2652 | 6.9901 |
0.0333 | 1.81 | 1400 | 0.2646 | 6.8727 |
0.0342 | 1.93 | 1500 | 0.2663 | 7.4894 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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