Whisper Tiny En - Entertainment - Game Commentary
This model is a fine-tuned version of openai/whisper-tiny on the fineaudio-Entertainment-Game Commentary dataset. It achieves the following results on the evaluation set:
- Loss: 0.8782
- Wer: 44.6354
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | Wer |
---|---|---|---|---|
0.7661 | 0.5984 | 1000 | 0.9245 | 49.5708 |
0.5931 | 1.1969 | 2000 | 0.8876 | 48.4366 |
0.5748 | 1.7953 | 3000 | 0.8788 | 44.2101 |
0.4717 | 2.3938 | 4000 | 0.8782 | 44.6354 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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Base model
openai/whisper-tinyEvaluation results
- Wer on fineaudio-Entertainment-Game Commentaryself-reported44.635