Whisper Small Ja-Qve - cportoca
This model is a fine-tuned version of openai/whisper-small on the Quechua_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2232
- Wer: 19.7678
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: 8
- seed: 42
- 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
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2739 | 1.3550 | 1000 | 0.3388 | 31.3461 |
| 0.1322 | 2.7100 | 2000 | 0.2377 | 25.1961 |
| 0.0275 | 4.0650 | 3000 | 0.2216 | 20.6464 |
| 0.0127 | 5.4201 | 4000 | 0.2232 | 19.7678 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- 6
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for cportoca/whisper-small-hi
Base model
openai/whisper-small