---
language:
- hr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-mici-princ
  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-mici-princ

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Mići Princ dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4596
- Wer: 33.5008

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3090
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0013        | 17.66  | 309  | 1.1495          | 37.1859 |
| 0.0009        | 35.31  | 618  | 1.1700          | 27.3032 |
| 0.0001        | 52.97  | 927  | 1.3428          | 27.7219 |
| 0.0001        | 70.63  | 1236 | 1.3874          | 27.2194 |
| 0.0001        | 88.29  | 1545 | 1.4141          | 27.3869 |
| 0.0001        | 105.94 | 1854 | 1.4331          | 33.5008 |
| 0.0001        | 123.6  | 2163 | 1.4445          | 33.3333 |
| 0.0           | 141.26 | 2472 | 1.4520          | 33.3333 |
| 0.0           | 158.91 | 2781 | 1.4576          | 33.3333 |
| 0.0           | 176.57 | 3090 | 1.4596          | 33.5008 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2