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---
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
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