metadata
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
Whisper Tiny PL
This model is a fine-tuned version of 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