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---
language:
- be
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Belarusian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 be
type: mozilla-foundation/common_voice_11_0
config: be
split: validation
args: be
metrics:
- name: Wer
type: wer
value: 6.3671568743912
---
<!-- 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 Belarusian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0706
- Wer: 6.3672
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- 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: 12000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1907 | 0.08 | 1000 | 0.2546 | 25.4639 |
| 0.1482 | 0.17 | 2000 | 0.1641 | 17.1676 |
| 0.1175 | 0.25 | 3000 | 0.1454 | 15.5940 |
| 0.0958 | 0.33 | 4000 | 0.1261 | 13.2625 |
| 0.099 | 0.42 | 5000 | 0.1012 | 10.6143 |
| 0.028 | 1.05 | 6000 | 0.1053 | 9.8794 |
| 0.0473 | 1.13 | 7000 | 0.1029 | 10.3078 |
| 0.0391 | 1.21 | 8000 | 0.0924 | 9.2419 |
| 0.0423 | 1.3 | 9000 | 0.0797 | 7.9249 |
| 0.0604 | 1.38 | 10000 | 0.0688 | 7.0150 |
| 0.0121 | 2.01 | 11000 | 0.0696 | 6.4638 |
| 0.0155 | 2.1 | 12000 | 0.0706 | 6.3672 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|