whisper-small-dar

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_17_0 ar dataset. It achieves the following results on the evaluation set:

• Loss: 0.1813
• Wer: 0.3367

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: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.303	0.5935	200	0.2434	0.4226
0.2	1.1869	400	0.2035	0.3914
0.1633	1.7804	600	0.1876	0.3469
0.106	2.3739	800	0.1850	0.3488
0.1005	2.9674	1000	0.1813	0.3367

Framework versions

• Transformers 4.48.0.dev0
• Pytorch 2.4.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0