whisper-small-splitted
This model is a fine-tuned version of openai/whisper-small on the Leonel-Maia/fongbe-splitted dataset. It achieves the following results on the evaluation set:
- Loss: 0.1084
- Wer: 0.1126
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: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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
- num_epochs: 60.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1324 | 2.1094 | 500 | 0.1909 | 0.3307 |
0.0383 | 4.2187 | 1000 | 0.1153 | 0.1131 |
0.0184 | 6.3281 | 1500 | 0.1084 | 0.1126 |
0.0098 | 8.4374 | 2000 | 0.1122 | 0.1014 |
0.0076 | 10.5468 | 2500 | 0.1101 | 0.0966 |
0.0075 | 12.6562 | 3000 | 0.1156 | 0.0992 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Base model
openai/whisper-small