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whisper-tiny-swc-drc-kat-2
This model is a fine-tuned version of openai/whisper-medium on the Ussen/swc-drc-katanga dataset. It achieves the following results on the evaluation set:
- Loss: 0.8770
- Wer Ortho: 39.7101
- Wer: 0.3914
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3735 | 2.96 | 1000 | 0.6459 | 48.5374 | 0.4783 |
| 0.081 | 5.93 | 2000 | 0.7478 | 38.5969 | 0.3797 |
| 0.0279 | 8.89 | 3000 | 0.8653 | 38.7523 | 0.3813 |
| 0.0189 | 11.85 | 4000 | 0.8770 | 39.7101 | 0.3914 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.13.1
- Tokenizers 0.12.1
