---
license: apache-2.0
tags:
- automatic-speech-recognition
- whisper
- romanian
datasets:
- readerbench/echo
metrics:
- wer
model-index:
- name: whisper-ro
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Echo
      type: readerbench/echo
      config: ro
    metrics:
    - name: WER
      type: wer
      value: 0.08668345828147764
---

# whisper-ro

This model is a fine-tuned version of
[openai/whisper-small](https://huggingface.co/openai/whisper-small) on the [Echo
dataset](https://huggingface.co/datasets/readerbench/echo), a large open-source
Romanian dataset.

| Name         | Small | Large-v2 | Fine-tuned small <br/><small>(this model)</small> |
|:------------:|:-----:|:--------:|:-------------------------------------------------:|
| Common Voice |  33.2 |     15.8 |                                              12.2 |
| FLEURS       |  29.8 |     14.4 |                                              10.9 |
| VoxPopuli    |  28.6 |     14.4 |                                               9.4 |
| Echo         |  >100 |     >100 |                                               8.6 |
| RSC          |  38.6 |     28.5 |                                               5.4 |

### Training hyperparameters

The following hyperparameters were used during training:

- `learning_rate`: 1e-05
- `train_batch_size`: 128
- `eval_batch_size`: 128
- `seed`: 42
- `distributed_type`: multi-GPU
- `num_devices`: 2
- `total_train_batch_size`: 256
- `total_eval_batch_size`: 256
- `optimizer`: Adam with betas=(0.9,0.999) and epsilon=1e-08
- `lr_scheduler_type`: linear
- `lr_scheduler_warmup_steps`: 500
- `num_epochs`: 20.0
- `mixed_precision_training`: Native AMP