---
language:
- ro
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large_v2 RO CV17
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 47.51015670342426
---

<!-- 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_v2 RO CV17

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6152
- Wer: 47.5102

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5004        | 5.4945  | 1000 | 1.1554          | 106.2565 |
| 0.0896        | 10.9890 | 2000 | 1.3810          | 51.0737  |
| 0.0121        | 16.4835 | 3000 | 1.5371          | 49.9013  |
| 0.0027        | 21.9780 | 4000 | 1.5901          | 49.1468  |
| 0.0008        | 27.4725 | 5000 | 1.6152          | 47.5102  |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.19.1