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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 Base 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: 12.206885082321635
---
<!-- 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 Base Belarusian
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_11_0 be dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1080
- Wer: 12.2069
## 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: 32
- 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: 6000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2445 | 0.17 | 1000 | 0.3059 | 32.4163 |
| 0.1823 | 0.33 | 2000 | 0.2004 | 22.1259 |
| 0.1412 | 0.5 | 3000 | 0.1752 | 20.0700 |
| 0.1093 | 0.67 | 4000 | 0.1413 | 16.0533 |
| 0.1137 | 0.83 | 5000 | 0.1155 | 13.3108 |
| 0.0585 | 1.1 | 6000 | 0.1080 | 12.2069 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|