whisper-base-zza

This model is a fine-tuned version of openai/whisper-base on the razhan/DOLMA-speech zazaki dataset. It achieves the following results on the evaluation set:

• Loss: 4.0956
• Wer: 1.2574
• Cer: 1.0132

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: 192
• eval_batch_size: 128
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 384
• total_eval_batch_size: 256
• 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: 1
• num_epochs: 5.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
No log	1.0	1	4.7831	1.2622	1.0146
No log	2.0	2	4.7831	1.2622	1.0146
No log	3.0	3	4.7831	1.2622	1.0146
No log	4.0	4	4.7831	1.2622	1.0146
No log	5.0	5	4.0956	1.2574	1.0132

Framework versions

• Transformers 4.49.0.dev0
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0