| --- |
| library_name: transformers |
| language: |
| - pl |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_17_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Tiny PL |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17 |
| type: mozilla-foundation/common_voice_17_0 |
| config: pl |
| split: None |
| args: pl |
| metrics: |
| - name: Wer |
| type: wer |
| value: 66.70131875965308 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Whisper Tiny PL |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6714 |
| - Wer Ortho: 75.9211 |
| - Wer: 66.7013 |
|
|
| ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: constant_with_warmup |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
| | 0.5684 | 0.7716 | 500 | 0.7197 | 103.1812 | 76.3039 | |
| | 0.4006 | 1.5432 | 1000 | 0.6714 | 79.3973 | 64.9667 | |
| | 0.2894 | 2.3148 | 1500 | 0.6739 | 78.6396 | 65.9231 | |
| | 0.2095 | 3.0864 | 2000 | 0.6714 | 75.9211 | 66.7013 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.50.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.4.1 |
| - Tokenizers 0.21.1 |
| |
