metadata
language:
- tr
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: base Turkish Whisper (bTW)
results: []
base Turkish Whisper (bTW)
This model is a fine-tuned version of openai/whisper-base on the Ermetal Meetings dataset. It achieves the following results on the evaluation set:
- Loss: 1.0034
- Wer: 0.9507
- Cer: 0.9543
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 |
|---|---|---|---|---|---|
| 1.6746 | 2.63 | 100 | 1.4311 | 0.8342 | 0.5210 |
| 0.7117 | 5.26 | 200 | 0.8645 | 0.9008 | 0.5476 |
| 0.4373 | 7.89 | 300 | 0.7748 | 0.7412 | 0.5489 |
| 0.2419 | 10.53 | 400 | 0.7788 | 0.6967 | 0.4042 |
| 0.1359 | 13.16 | 500 | 0.8320 | 0.6912 | 0.5735 |
| 0.055 | 15.79 | 600 | 0.8891 | 0.7571 | 0.7292 |
| 0.0268 | 18.42 | 700 | 0.9250 | 0.7480 | 0.6051 |
| 0.0133 | 21.05 | 800 | 0.9747 | 0.6906 | 0.7730 |
| 0.0088 | 23.68 | 900 | 0.9968 | 0.8349 | 0.8106 |
| 0.0077 | 26.32 | 1000 | 1.0034 | 0.9507 | 0.9543 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2