Hugging Face's logo

Arbi-Houssem
/
TunLangModel_test1.16

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
TunLangModel_test1.16 / README.md
Arbi-Houssem's picture
Arbi-Houssem
End of training
f28cfe0 verified
preview code
|
raw history blame contribute delete
No virus
2.35 kB
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: 90.7904174436953

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: 1.8540
  • Wer: 90.7904

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-08
  • 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
2.2076 4.5045 500 2.1992 120.4131
2.0416 9.0090 1000 2.0813 117.6732
1.9182 13.5135 1500 1.9770 119.2368
1.9273 18.0180 2000 1.9219 104.0023
1.8201 22.5225 2500 1.8901 94.8931
1.7708 27.0270 3000 1.8667 92.9709
1.7865 31.5315 3500 1.8565 90.8908
1.805 36.0360 4000 1.8540 90.7904

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1