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---
language:
- ru
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- tbkazakova/even_speech_biblical
metrics:
- wer
model-index:
- name: Whisper Small Even - VovaK13
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Even Speech Biblical
type: tbkazakova/even_speech_biblical
config: default
split: None
args: 'config: ru, split: train'
metrics:
- name: Wer
type: wer
value: 30.275689223057643
---
<!-- 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 Even - VovaK13
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Even Speech Biblical dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4483
- Wer: 30.2757
## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0509 | 5.9880 | 500 | 0.3699 | 33.7343 |
| 0.0022 | 11.9760 | 1000 | 0.4084 | 30.9273 |
| 0.0003 | 17.9641 | 1500 | 0.4336 | 30.1253 |
| 0.0002 | 23.9521 | 2000 | 0.4444 | 30.2757 |
| 0.0002 | 29.9401 | 2500 | 0.4483 | 30.2757 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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