|
|
--- |
|
|
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: 1.1836 |
|
|
- Wer: 1.7109 |
|
|
- Cer: 1.2860 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
|
| 1.7878 | 4.74 | 100 | 1.4516 | 0.8560 | 0.5525 | |
|
|
| 0.6701 | 9.51 | 200 | 0.9194 | 0.8543 | 0.6112 | |
|
|
| 0.3364 | 14.28 | 300 | 0.8871 | 0.7415 | 0.4992 | |
|
|
| 0.1228 | 19.05 | 400 | 0.9671 | 0.9052 | 0.6678 | |
|
|
| 0.0355 | 23.78 | 500 | 1.0515 | 0.8961 | 0.6208 | |
|
|
| 0.0148 | 28.55 | 600 | 1.0684 | 0.6644 | 0.3694 | |
|
|
| 0.0056 | 33.32 | 700 | 1.1488 | 1.3315 | 0.8732 | |
|
|
| 0.0041 | 38.09 | 800 | 1.1700 | 1.7415 | 1.1934 | |
|
|
| 0.0034 | 42.83 | 900 | 1.1801 | 1.7745 | 1.2643 | |
|
|
| 0.0032 | 47.6 | 1000 | 1.1836 | 1.7109 | 1.2860 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.26.0 |
|
|
- Pytorch 1.12.0+cu102 |
|
|
- Datasets 2.9.0 |
|
|
- Tokenizers 0.13.2 |
|
|
|
