---
library_name: peft
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: model
  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. -->

# model

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: 0.0984
- Wer: 12.1817

## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0432        | 4.2373  | 1000 | 0.0928          | 13.0043 |
| 0.0211        | 8.4746  | 2000 | 0.0946          | 13.2132 |
| 0.0126        | 12.7119 | 3000 | 0.0959          | 12.5996 |
| 0.0136        | 16.9492 | 4000 | 0.0984          | 12.1817 |


### Framework versions

- PEFT 0.17.1
- Transformers 4.55.2
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4