k-seungri/k_whisper_model
This model is a fine-tuned version of openai/whisper-base on the k_whisper_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.6590
- Cer: 53.0478
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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
0.0002 | 142.86 | 1000 | 0.5964 | 16.9687 |
0.0001 | 285.71 | 2000 | 0.6299 | 16.6392 |
0.0001 | 428.57 | 3000 | 0.6459 | 17.1334 |
0.0001 | 571.43 | 4000 | 0.6590 | 53.0478 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for k-seungri/k_whisper_output
Base model
openai/whisper-base