metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
metrics:
- wer
model-index:
- name: Whisper Tunisien
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Tunisian_dataset_STT-TTS15s_filtred1.0
type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 117.69074949358543
Whisper Tunisien
This model is a fine-tuned version of openai/whisper-base on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 4.7577
- Wer: 117.6907
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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5147 | 7.7519 | 500 | 3.1417 | 128.5618 |
| 0.0559 | 15.5039 | 1000 | 3.8111 | 132.5456 |
| 0.01 | 23.2558 | 1500 | 4.2115 | 120.1891 |
| 0.0029 | 31.0078 | 2000 | 4.4628 | 120.3916 |
| 0.0017 | 38.7597 | 2500 | 4.6127 | 111.2086 |
| 0.0011 | 46.5116 | 3000 | 4.6945 | 124.6455 |
| 0.0009 | 54.2636 | 3500 | 4.7426 | 113.3018 |
| 0.0009 | 62.0155 | 4000 | 4.7577 | 117.6907 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1