---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-polish-impaired
  results: []
---

<!-- 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-large-v3-polish-impaired

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5641
- Wer: 83.0040

## 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 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_steps: 50
- training_steps: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.239         | 0.05  | 1    | 2.7489          | 84.5850 |
| 1.8286        | 0.1   | 2    | 2.7304          | 84.5850 |
| 2.1458        | 0.15  | 3    | 2.6956          | 84.5850 |
| 2.5037        | 0.2   | 4    | 2.6399          | 83.3992 |
| 2.5533        | 0.25  | 5    | 2.5641          | 83.0040 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0