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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 Tiny 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: 46.52014652014652
---
<!-- 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 Tiny Belarusian
Repo to test model training
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 be dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4388
- Wer: 46.5201
## 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: 32
- 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: 10
- training_steps: 300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.5366 | 0.05 | 10 | 1.5402 | 94.5055 |
| 1.3721 | 0.1 | 20 | 1.0021 | 75.8242 |
| 0.9921 | 0.15 | 30 | 0.8322 | 75.0916 |
| 0.9844 | 0.2 | 40 | 0.8080 | 72.8938 |
| 0.7071 | 0.25 | 50 | 0.7862 | 77.2894 |
| 0.7998 | 0.3 | 60 | 0.7052 | 68.8645 |
| 0.6935 | 0.35 | 70 | 0.6781 | 64.2857 |
| 0.81 | 0.4 | 80 | 0.6341 | 63.5531 |
| 0.6133 | 0.45 | 90 | 0.6083 | 62.6374 |
| 0.6675 | 0.5 | 100 | 0.5851 | 62.8205 |
| 0.5577 | 0.55 | 110 | 0.5651 | 59.3407 |
| 0.6473 | 0.6 | 120 | 0.5638 | 58.0586 |
| 0.6018 | 0.65 | 130 | 0.5434 | 53.8462 |
| 0.5918 | 0.7 | 140 | 0.5385 | 54.9451 |
| 0.5654 | 0.75 | 150 | 0.5200 | 58.0586 |
| 0.587 | 0.8 | 160 | 0.4974 | 57.1429 |
| 0.6157 | 0.85 | 170 | 0.4834 | 53.2967 |
| 0.6803 | 0.9 | 180 | 0.4852 | 55.8608 |
| 0.4813 | 0.95 | 190 | 0.4686 | 51.2821 |
| 0.4952 | 1.0 | 200 | 0.4624 | 51.4652 |
| 0.3956 | 0.03 | 210 | 0.4690 | 52.0147 |
| 0.3719 | 0.07 | 220 | 0.4673 | 52.7473 |
| 0.3168 | 0.1 | 230 | 0.4499 | 51.4652 |
| 0.3582 | 0.13 | 240 | 0.4525 | 46.8864 |
| 0.2475 | 0.17 | 250 | 0.4612 | 52.3810 |
| 0.2988 | 0.2 | 260 | 0.4346 | 49.8168 |
| 0.2749 | 0.23 | 270 | 0.4249 | 48.9011 |
| 0.3368 | 0.27 | 280 | 0.4388 | 46.5201 |
| 0.2574 | 0.3 | 290 | 0.4309 | 46.7033 |
| 0.2921 | 0.33 | 300 | 0.4282 | 46.7033 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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