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---
language:
- tr
license: apache-2.0
tags:
- whisper
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Turkish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 tr
type: mozilla-foundation/common_voice_11_0
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 17.275280898876407
---
<!-- 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 Turkish
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 tr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2799
- Wer: 17.2753
- Cer: 4.5335
## 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: 16
- 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.1044 | 1.07 | 1000 | 0.2777 | 18.4046 | 4.8810 |
| 0.0469 | 3.02 | 2000 | 0.2799 | 17.2753 | 4.5335 |
| 0.014 | 4.09 | 3000 | 0.3202 | 18.0800 | 4.9039 |
| 0.0039 | 6.04 | 4000 | 0.3326 | 18.2964 | 5.0192 |
| 0.0022 | 7.11 | 5000 | 0.3453 | 18.0307 | 4.9470 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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