Common Voice 16 - Guarani
This model is a fine-tuned version of openai/whisper-base on the Common Voice 16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5929
- Cer: 13.2243
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 2.3402 | 1.0101 | 100 | 0.9377 | 20.2765 |
| 0.5917 | 2.0202 | 200 | 0.6871 | 16.3785 |
| 0.3349 | 3.0303 | 300 | 0.6126 | 15.5452 |
| 0.2024 | 4.0404 | 400 | 0.5887 | 14.1160 |
| 0.1236 | 5.0505 | 500 | 0.5929 | 13.2243 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Downloads last month
- 4