---
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_17_0_romanian_speech_synthesis
metrics:
- wer
model-index:
- name: Whisper Small Ro - Sarbu Vlad - multi gpu --> 3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0 + Romanian speech synthesis
      type: VladS159/common_voice_17_0_romanian_speech_synthesis
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 10.55709542810149
---

<!-- 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 Small Ro - Sarbu Vlad - multi gpu --> 3

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 + Romanian speech synthesis dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1249
- Wer: 10.5571

## 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: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 48
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2432        | 0.68  | 500  | 0.2134          | 19.7435 |
| 0.137         | 1.36  | 1000 | 0.1532          | 15.5189 |
| 0.0672        | 2.04  | 1500 | 0.1287          | 13.0426 |
| 0.0579        | 2.72  | 2000 | 0.1218          | 12.8659 |
| 0.0307        | 3.4   | 2500 | 0.1183          | 11.9887 |
| 0.0167        | 4.08  | 3000 | 0.1177          | 11.5866 |
| 0.016         | 4.76  | 3500 | 0.1149          | 10.9531 |
| 0.0099        | 5.43  | 4000 | 0.1212          | 10.9713 |
| 0.0058        | 6.11  | 4500 | 0.1216          | 10.8251 |
| 0.0056        | 6.79  | 5000 | 0.1224          | 10.6515 |
| 0.0036        | 7.47  | 5500 | 0.1238          | 10.6211 |
| 0.0035        | 8.15  | 6000 | 0.1249          | 10.5571 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1