---
language:
- ru
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-tiny
datasets:
- bond005/podlodka_speech
metrics:
- wer
model-index:
- name: whisper-tiny-ru
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Podlodka Speech
      type: bond005/podlodka_speech
      args: 'config: ru, split: test'
    metrics:
    - type: wer
      value: 83.72703412073491
      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-tiny-ru

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Podlodka Speech dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2475
- Wer: 83.7270

## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 200

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9999        | 4.4444  | 40   | 1.2054          | 71.8285  |
| 0.4535        | 8.8889  | 80   | 1.1539          | 73.2283  |
| 0.2849        | 13.3333 | 120  | 1.1958          | 104.5494 |
| 0.1674        | 17.7778 | 160  | 1.2341          | 79.2651  |
| 0.1372        | 22.2222 | 200  | 1.2475          | 83.7270  |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1