metadata
library_name: transformers
language:
- pl
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-med-pl
results: []
whisper-small-med-pl
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7463
- Wer: 44.2464
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8305 | 0.4954 | 108 | 0.8192 | 55.6976 |
| 0.7908 | 0.9908 | 216 | 0.7731 | 49.3476 |
| 0.7031 | 1.4862 | 324 | 0.7591 | 47.6053 |
| 0.6715 | 1.9817 | 432 | 0.7479 | 49.9371 |
| 0.6193 | 2.4771 | 540 | 0.7478 | 47.1537 |
| 0.6019 | 2.9725 | 648 | 0.7463 | 44.2464 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.21.4