---
language:
- ru
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 'Whisper Small Ru ORD 0.4 - Mizoru '
  results: []
---

<!-- 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 Ru ORD 0.4 - Mizoru 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ORD_0.4 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0157
- Wer: 47.4481
- Cer: 27.9353
- Clean Wer: 38.8041
- Clean Cer: 22.5075

## 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     | Cer     | Clean Wer | Clean Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:---------:|:---------:|
| 1.0606        | 1.0   | 573  | 1.0674          | 50.9989 | 29.8675 | 41.9998   | 24.3296   |
| 0.9142        | 2.0   | 1146 | 1.0090          | 48.2571 | 28.1474 | 39.9670   | 22.7534   |
| 0.7999        | 3.0   | 1719 | 1.0020          | 48.5513 | 28.3688 | 39.3516   | 22.9446   |
| 0.6655        | 4.0   | 2292 | 1.0157          | 47.4481 | 27.9353 | 38.8041   | 22.5075   |
| 0.5702        | 5.0   | 2865 | 1.0444          | 48.1203 | 28.1053 | 39.3807   | 22.5587   |
| 0.4817        | 6.0   | 3438 | 1.0735          | 47.8894 | 27.9447 | 39.2281   | 22.3609   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.2