gwanju_medium2_model
This model is a fine-tuned version of openai/whisper-medium on the Marcusxx/gwanju dataset. It achieves the following results on the evaluation set:
- Loss: 0.3592
- Cer: 44.1724
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: 250
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
0.4478 | 0.2964 | 1000 | 0.4342 | 48.5130 |
0.3965 | 0.5928 | 2000 | 0.3973 | 401.9235 |
0.3913 | 0.8892 | 3000 | 0.3777 | 23.1253 |
0.236 | 1.1855 | 4000 | 0.3685 | 27.0142 |
0.2617 | 1.4819 | 5000 | 0.3638 | 31.4542 |
0.2245 | 1.7783 | 6000 | 0.3556 | 24.0368 |
0.1363 | 2.0747 | 7000 | 0.3582 | 27.9426 |
0.1232 | 2.3711 | 8000 | 0.3629 | 29.3680 |
0.1299 | 2.6675 | 9000 | 0.3615 | 40.2485 |
0.1191 | 2.9638 | 10000 | 0.3592 | 44.1724 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-medium