AdaCodruta/whisper_ro_MilDB

Whisper Large_v2 RO CV17

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

• Loss: 1.6152
• Wer: 47.5102

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: 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: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5004	5.4945	1000	1.1554	106.2565
0.0896	10.9890	2000	1.3810	51.0737
0.0121	16.4835	3000	1.5371	49.9013
0.0027	21.9780	4000	1.5901	49.1468
0.0008	27.4725	5000	1.6152	47.5102

Framework versions

• Transformers 4.40.2
• Pytorch 2.5.1+cu118
• Datasets 3.1.0
• Tokenizers 0.19.1