---
language:
- ru
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Ru
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0
      type: mozilla-foundation/common_voice_16_0
      config: ru
      split: None
      args: 'config: ru, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 151.55619160645514
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3411
- Wer: 151.5562

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3519        | 0.61  | 1000 | 0.3882          | 155.8949 |
| 0.2055        | 1.21  | 2000 | 0.3565          | 159.1748 |
| 0.2047        | 1.82  | 3000 | 0.3422          | 164.2338 |
| 0.1469        | 2.43  | 4000 | 0.3411          | 151.5562 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.1