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---
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Serbian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: sr
split: test
args: sr
metrics:
- name: Wer
type: wer
value: 17.41963509991312
---
<!-- 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 Serbian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4671
- Wer Ortho: 27.4565
- Wer: 17.4196
## 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: 50
- training_steps: 2500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.1403 | 1.44 | 250 | 0.2809 | 28.8913 | 19.2224 |
| 0.0664 | 2.87 | 500 | 0.2858 | 27.3696 | 17.9626 |
| 0.0315 | 4.31 | 750 | 0.3152 | 27.9348 | 17.4631 |
| 0.0174 | 5.75 | 1000 | 0.3578 | 28.1522 | 17.9844 |
| 0.0067 | 7.18 | 1250 | 0.4018 | 27.9130 | 17.9626 |
| 0.0015 | 8.62 | 1500 | 0.4535 | 28.6739 | 17.5717 |
| 0.0008 | 10.06 | 1750 | 0.4558 | 27.2174 | 17.1807 |
| 0.0005 | 11.49 | 2000 | 0.4585 | 27.4348 | 17.4848 |
| 0.0005 | 12.93 | 2250 | 0.4651 | 27.3478 | 17.3979 |
| 0.0005 | 14.37 | 2500 | 0.4671 | 27.4565 | 17.4196 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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