|
|
--- |
|
|
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: 1.9500 |
|
|
- Wer: 2.1895 |
|
|
- Cer: 1.3548 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
|
| 1.7116 | 5.53 | 100 | 1.9115 | 1.1785 | 0.6901 | |
|
|
| 0.6101 | 11.11 | 200 | 1.5123 | 1.1039 | 0.6221 | |
|
|
| 0.2376 | 16.64 | 300 | 1.5636 | 0.9817 | 0.6448 | |
|
|
| 0.0591 | 22.21 | 400 | 1.7179 | 2.2005 | 1.3384 | |
|
|
| 0.0177 | 27.75 | 500 | 1.8454 | 1.9205 | 1.2140 | |
|
|
| 0.0096 | 33.32 | 600 | 1.8529 | 1.2983 | 0.7777 | |
|
|
| 0.0048 | 38.85 | 700 | 1.9306 | 2.3411 | 1.4385 | |
|
|
| 0.0032 | 44.43 | 800 | 1.9388 | 1.9523 | 1.2705 | |
|
|
| 0.0028 | 49.96 | 900 | 1.9472 | 1.8655 | 1.2023 | |
|
|
| 0.0026 | 55.53 | 1000 | 1.9500 | 2.1895 | 1.3548 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.26.0 |
|
|
- Pytorch 1.12.0+cu102 |
|
|
- Datasets 2.9.0 |
|
|
- Tokenizers 0.13.2 |
|
|
|
