---
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Romanian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Romanian voice 1.0
      type: mozilla-foundation/common_voice_11_0
      config: ro
      split: test
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 42.218080149114634
---

<!-- 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 Romanian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Romanian voice 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3430
- Wer: 42.2181

## 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: 0.0001
- train_batch_size: 8
- 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: 250
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.396         | 0.9   | 1000 | 0.5565          | 88.6587 |
| 0.187         | 1.8   | 2000 | 0.4436          | 53.4841 |
| 0.0744        | 2.7   | 3000 | 0.3862          | 53.7279 |
| 0.0222        | 3.6   | 4000 | 0.3430          | 42.2181 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.6.1
- Tokenizers 0.15.0