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whisper-small-ko-normalized-1273h
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1426
- Wer: 0.0671
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0726 | 1.0 | 6581 | 0.1490 | 0.0721 |
0.0368 | 2.0 | 13162 | 0.1405 | 0.0686 |
0.0317 | 3.0 | 19743 | 0.1426 | 0.0671 |
Framework versions
-
Transformers 4.28.0.dev0
-
Pytorch 1.13.1+cu117
-
Datasets 2.11.0
-
Tokenizers 0.13.2
-
Evaluation Result for the dataset
google/fleurs
The trained model is evaluated on the test
split of subset ko_kr
from the dataset google/fleurs
.
Please note that the model was not trained on the train
split from the dataset.
model | Wer |
---|---|
openai/whisper | 0.2826 |
this model | 0.2679 |