---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper-large-v3-croarian_overlap_removed_30
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 82.7174045615319
---

<!-- 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-croarian_overlap_removed_30

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5767
- Wer: 82.7174

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0275        | 22.22 | 1000 | 2.2397          | 76.3508 |
| 0.0075        | 44.44 | 2000 | 2.3756          | 75.8507 |
| 0.0024        | 66.67 | 3000 | 2.5384          | 83.9005 |
| 0.0021        | 88.89 | 4000 | 2.5767          | 82.7174 |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1