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---
language:
- ba
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Bashkir
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ba
type: mozilla-foundation/common_voice_11_0
config: ba
split: test
args: ba
metrics:
- name: Wer
type: wer
value: 15.072300680807968
---
<!-- 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 Bashkir
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 ba dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2589
- Wer: 15.0723
## 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: 8
- 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: 30000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1637 | 1.01 | 2000 | 0.2555 | 26.4682 |
| 0.1375 | 2.01 | 4000 | 0.2223 | 21.5394 |
| 0.0851 | 3.02 | 6000 | 0.2086 | 19.6725 |
| 0.0573 | 4.02 | 8000 | 0.2178 | 18.4280 |
| 0.036 | 5.03 | 10000 | 0.2312 | 17.8248 |
| 0.0238 | 6.04 | 12000 | 0.2621 | 17.4096 |
| 0.0733 | 7.04 | 14000 | 0.2120 | 16.5656 |
| 0.0111 | 8.05 | 16000 | 0.2682 | 16.2291 |
| 0.0155 | 9.05 | 18000 | 0.2677 | 15.9242 |
| 0.0041 | 10.06 | 20000 | 0.3178 | 15.9534 |
| 0.0023 | 12.01 | 22000 | 0.3218 | 16.0536 |
| 0.0621 | 13.01 | 24000 | 0.2313 | 15.6169 |
| 0.0022 | 14.02 | 26000 | 0.2887 | 15.1083 |
| 0.0199 | 15.02 | 28000 | 0.2553 | 15.1848 |
| 0.0083 | 16.03 | 30000 | 0.2589 | 15.0723 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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