---
library_name: transformers
language:
- pl
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- classla/ParlaSpeech-PL
metrics:
- wer
model-index:
- name: Whisper Small Pl - Jan Stusio
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ParlaSpeech Pl
      type: classla/ParlaSpeech-PL
      args: 'config: pl, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 69.04761904761905
---

<!-- 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 Small Pl - Jan Stusio

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ParlaSpeech Pl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4903
- Wer: 69.0476

## 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: 1
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use adamw_torch_fused 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: 10
- training_steps: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3228        | 6.32  | 25   | 0.4705          | 70.8333 |
| 0.0071        | 12.64 | 50   | 0.4903          | 69.0476 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0
- Datasets 4.3.0
- Tokenizers 0.22.1