---
language:
- ru
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Ru - Swedish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: default
      split: test
      args: 'config: ru, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 27.381068672462632
---

<!-- 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 Base Ru - Swedish

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3077
- Wer: 27.3811

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2882        | 0.49  | 1000 | 0.3627          | 30.3885 |
| 0.2675        | 0.98  | 2000 | 0.3264          | 28.4422 |
| 0.1765        | 1.48  | 3000 | 0.3146          | 27.6424 |
| 0.1757        | 1.97  | 4000 | 0.3077          | 27.3811 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 1.13.1
- Datasets 2.15.0
- Tokenizers 0.15.0