whisper-small-ar-12hrsdarijadata-April29

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9985
• Wer: 77.7026
• Cer: 48.3376

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: 1.25e-06
• train_batch_size: 16
• 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: 300
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.8036	0.38	250	1.4314	92.8372	55.4587
1.3528	0.75	500	1.1339	79.2413	48.2563
1.1316	1.13	750	1.0272	76.8802	49.5272
1.1439	1.51	1000	0.9985	77.7026	48.3376

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.0+cu118
• Datasets 2.12.1.dev0
• Tokenizers 0.13.3