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---
language:
- bg
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: openai/whisper-small-finetuned-common_voice_13_0-bg
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0
type: mozilla-foundation/common_voice_13_0
config: bg
split: test
args: bg
metrics:
- name: Wer
type: wer
value: 23.264792642720806
---
<!-- 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. -->
# openai/whisper-small-finetuned-common_voice_13_0-bg
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3983
- Wer Ortho: 30.2504
- Wer: 23.2648
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.0787 | 2.78 | 500 | 0.3445 | 31.2999 | 24.2365 |
| 0.0145 | 5.56 | 1000 | 0.3983 | 30.2504 | 23.2648 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.0+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0
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