---
library_name: peft
language:
- pl
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- base_model:adapter:openai/whisper-large-v3-turbo
- lora
- transformers
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-med-pl-lora-r16-decoder-only-lr5e-05-ep3-whisper_fair
  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-turbo-med-pl-lora-r16-decoder-only-lr5e-05-ep3-whisper_fair

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6611
- Model Preparation Time: 0.0094
- Wer: 14.1952
- Cer: 4.3217
- Content Wer: 8.0298

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer     | Cer    | Content Wer |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:|:------:|:-----------:|
| 1.6854        | 1.0   | 1514 | 1.6789          | 0.0094                 | 15.3443 | 4.6216 | 8.6227      |
| 1.673         | 2.0   | 3028 | 1.6657          | 0.0094                 | 14.5163 | 4.3504 | 8.1569      |
| 1.6675        | 3.0   | 4542 | 1.6611          | 0.0094                 | 14.1952 | 4.3217 | 8.0298      |


### Framework versions

- PEFT 0.18.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2