Incremental Swahili Luganda
This model is a fine-tuned version of openai/whisper-small on the Mix data dataset. It achieves the following results on the evaluation set:
- Loss: 0.3430
- Wer: 31.7183
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
---|---|---|---|---|
0.2355 | 0.0894 | 500 | 0.3831 | 35.9432 |
0.2275 | 0.1789 | 1000 | 0.3818 | 35.3379 |
0.245 | 0.2683 | 1500 | 0.3727 | 34.4346 |
0.2321 | 0.3577 | 2000 | 0.3637 | 33.5439 |
0.2396 | 0.4472 | 2500 | 0.3569 | 32.9164 |
0.2231 | 0.5366 | 3000 | 0.3512 | 33.0780 |
0.2039 | 0.6261 | 3500 | 0.3468 | 32.3184 |
0.2283 | 0.7155 | 4000 | 0.3430 | 31.7183 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small