metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- zw
metrics:
- wer
model-index:
- name: large-v3-turbo-zwksa1305
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: zwksa
type: zw
config: default
split: train
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 45.656877897990725
large-v3-turbo-zwksa1305
This model is a fine-tuned version of openai/whisper-large-v3 on the zwksa dataset. It achieves the following results on the evaluation set:
- Loss: 0.8594
- Wer: 45.6569
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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6356 | 0.8772 | 100 | 0.6373 | 51.2563 |
| 0.4797 | 1.7544 | 200 | 0.5798 | 47.8737 |
| 0.3037 | 2.6316 | 300 | 0.5865 | 45.8821 |
| 0.2044 | 3.5088 | 400 | 0.6082 | 45.5862 |
| 0.1288 | 4.3860 | 500 | 0.6568 | 45.0254 |
| 0.0734 | 5.2632 | 600 | 0.7035 | 45.7717 |
| 0.0558 | 6.1404 | 700 | 0.7563 | 46.1161 |
| 0.0367 | 7.0175 | 800 | 0.7771 | 45.0960 |
| 0.0196 | 7.8947 | 900 | 0.8203 | 46.0720 |
| 0.0137 | 8.7719 | 1000 | 0.8594 | 45.6569 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1