metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
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_Mixed
type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 53.55042318175298
Whisper Tunisien
This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed dataset. It achieves the following results on the evaluation set:
- Loss: 0.9262
- Wer: 53.5504
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 |
---|---|---|---|---|
1.0933 | 4.5045 | 500 | 1.1956 | 61.0242 |
0.7416 | 9.0090 | 1000 | 0.9971 | 56.0895 |
0.5403 | 13.5135 | 1500 | 0.9140 | 53.4644 |
0.4315 | 18.0180 | 2000 | 0.8778 | 53.3783 |
0.2836 | 22.5225 | 2500 | 0.8948 | 53.0627 |
0.2513 | 27.0270 | 3000 | 0.9099 | 53.5074 |
0.2196 | 31.5315 | 3500 | 0.9215 | 53.6365 |
0.2199 | 36.0360 | 4000 | 0.9262 | 53.5504 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1