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---
library_name: transformers
language:
- ru
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small ru - slowlydoor
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ru
split: None
args: 'config: ru, split: test'
metrics:
- name: Wer
type: wer
value: 16.67692593581956
---
<!-- 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 - slowlydoor
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1989
- Wer: 16.6769
- Cer: 4.3640
- Ser: 59.1591
## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Ser |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.2176 | 0.1516 | 500 | 0.2575 | 21.0009 | 5.4512 | 69.0581 |
| 0.2146 | 0.3032 | 1000 | 0.2395 | 19.7826 | 5.2221 | 66.5785 |
| 0.1817 | 0.4548 | 1500 | 0.2264 | 18.5724 | 4.7800 | 64.4320 |
| 0.1862 | 0.6064 | 2000 | 0.2140 | 18.2088 | 4.7904 | 62.3542 |
| 0.1618 | 0.7580 | 2500 | 0.2049 | 17.0765 | 4.3953 | 60.4234 |
| 0.1597 | 0.9096 | 3000 | 0.1989 | 16.6769 | 4.3640 | 59.1591 |
### Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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