---
language:
- ru
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Russian
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 ru
      type: mozilla-foundation/common_voice_11_0
      config: ru
      split: test
      args: ru
    metrics:
    - type: wer
      value: 7.562437929892964
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ru_ru
      split: test
    metrics:
    - type: wer
      value: 10.92
      name: WER
---

<!-- 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 Medium Russian

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 ru dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2253
- Wer: 7.5624

## 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: 16
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1578        | 0.1   | 1000  | 0.1662          | 8.8290 |
| 0.045         | 1.08  | 2000  | 0.1748          | 8.9148 |
| 0.0176        | 2.06  | 3000  | 0.1889          | 8.7848 |
| 0.0104        | 3.04  | 4000  | 0.1922          | 8.4354 |
| 0.0051        | 4.02  | 5000  | 0.2034          | 8.1865 |
| 0.0047        | 4.12  | 6000  | 0.2012          | 8.0455 |
| 0.0018        | 5.1   | 7000  | 0.2117          | 7.6237 |
| 0.0004        | 6.08  | 8000  | 0.2177          | 7.6078 |
| 0.0003        | 7.06  | 9000  | 0.2244          | 7.6262 |
| 0.0002        | 8.04  | 10000 | 0.2253          | 7.5624 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2