---
library_name: transformers
language:
- hr
license: apache-2.0
base_model: GoranS/whisper-large-v3-turbo-hr-parla
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo.hr
  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.hr

This model is a fine-tuned version of [GoranS/whisper-large-v3-turbo-hr-parla](https://huggingface.co/GoranS/whisper-large-v3-turbo-hr-parla) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1473
- Wer: 0.1155

## 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: 6.25e-06
- train_batch_size: 64
- eval_batch_size: 32
- 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
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.1629        | 0.5450 | 1000 | 0.1638          | 0.1151 |
| 0.1133        | 1.0899 | 2000 | 0.1513          | 0.1168 |
| 0.0979        | 1.6349 | 3000 | 0.1473          | 0.1155 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3