---
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: base Turkish Whisper (bTW)
  results: []
---

<!-- 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. -->

# base Turkish Whisper (bTW)

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Ermetal Meetings dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4238
- Wer: 0.9367
- Cer: 0.7611

## 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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.6918        | 2.85  | 100  | 1.5023          | 0.7940 | 0.4289 |
| 0.6823        | 5.71  | 200  | 1.0475          | 0.8783 | 0.5573 |
| 0.4277        | 8.57  | 300  | 0.9944          | 0.8054 | 0.6120 |
| 0.2244        | 11.43 | 400  | 1.0460          | 0.6878 | 0.3825 |
| 0.1138        | 14.28 | 500  | 1.2059          | 0.7510 | 0.5020 |
| 0.0468        | 17.14 | 600  | 1.2180          | 1.1436 | 1.0719 |
| 0.0193        | 19.99 | 700  | 1.2801          | 1.1500 | 0.9344 |
| 0.0093        | 22.85 | 800  | 1.4574          | 0.9238 | 0.6799 |
| 0.0068        | 25.71 | 900  | 1.4137          | 0.9400 | 0.8128 |
| 0.0062        | 28.57 | 1000 | 1.4238          | 0.9367 | 0.7611 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2