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Whisper Tiny AlphaDigit Decoder Finetune 10k Clean
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0615
- Wer: 58.8931
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: 16
- 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: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0987 | 0.51 | 1000 | 0.0878 | 90.7605 |
| 0.0745 | 1.03 | 2000 | 0.0737 | 91.3320 |
| 0.0647 | 1.54 | 3000 | 0.0689 | 83.4997 |
| 0.063 | 2.05 | 4000 | 0.0676 | 79.2696 |
| 0.0498 | 2.56 | 5000 | 0.0655 | 69.8125 |
| 0.0511 | 3.08 | 6000 | 0.0634 | 69.5636 |
| 0.0373 | 3.59 | 7000 | 0.0623 | 65.4287 |
| 0.0361 | 4.1 | 8000 | 0.0619 | 61.4768 |
| 0.0465 | 4.61 | 9000 | 0.0617 | 59.5491 |
| 0.0376 | 5.13 | 10000 | 0.0615 | 58.8931 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
