|
--- |
|
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: 0.0009 |
|
- Wer: 0.0 |
|
- Cer: 0.0 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 1.8786 | 6.63 | 100 | 1.3510 | 0.7866 | 0.6649 | |
|
| 0.4559 | 13.32 | 200 | 0.3395 | 0.3590 | 0.2157 | |
|
| 0.0793 | 19.95 | 300 | 0.0564 | 0.0996 | 0.0531 | |
|
| 0.0137 | 26.63 | 400 | 0.0120 | 0.0017 | 0.0017 | |
|
| 0.0042 | 33.32 | 500 | 0.0032 | 0.0 | 0.0 | |
|
| 0.0021 | 39.95 | 600 | 0.0018 | 0.0 | 0.0 | |
|
| 0.0014 | 46.63 | 700 | 0.0013 | 0.0 | 0.0 | |
|
| 0.0012 | 53.32 | 800 | 0.0011 | 0.0 | 0.0 | |
|
| 0.001 | 59.95 | 900 | 0.0010 | 0.0 | 0.0 | |
|
| 0.001 | 66.63 | 1000 | 0.0009 | 0.0 | 0.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.9.1+cu111 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|
