README.md

metadata

library_name: transformers
license: apache-2.0
base_model: Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - wer
model-index:
  - name: whisper-smal-ar-testing-kale
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: None
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 307.8198198198198

whisper-smal-ar-testing-kale

This model is a fine-tuned version of Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 2.6230
• Wer: 307.8198

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: 1
• training_steps: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.6566	0.0032	2	2.6230	307.8198

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.1