| --- |
| 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: 1.1451 |
| - Wer: 1.0165 |
| - Cer: 0.7894 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | 1.6901 | 4.54 | 100 | 1.3928 | 0.8093 | 0.4264 | |
| | 0.6163 | 9.09 | 200 | 0.8885 | 0.7907 | 0.4532 | |
| | 0.2692 | 13.63 | 300 | 0.8719 | 0.7823 | 0.4474 | |
| | 0.1148 | 18.18 | 400 | 0.9275 | 0.7393 | 0.4280 | |
| | 0.04 | 22.72 | 500 | 1.0308 | 0.8162 | 0.5241 | |
| | 0.0114 | 27.27 | 600 | 1.0885 | 0.9666 | 0.7902 | |
| | 0.0051 | 31.81 | 700 | 1.1159 | 0.9594 | 0.6967 | |
| | 0.0036 | 36.36 | 800 | 1.1301 | 1.0451 | 0.7819 | |
| | 0.0031 | 40.9 | 900 | 1.1415 | 1.0496 | 0.8072 | |
| | 0.0028 | 45.45 | 1000 | 1.1451 | 1.0165 | 0.7894 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.26.0 |
| - Pytorch 1.12.0+cu102 |
| - Datasets 2.9.0 |
| - Tokenizers 0.13.2 |
|
|
