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---
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
|