alikanakar/whisper-small-CV-43-freeze-encoder

Whisper Small Tr - CV 43h - Frozen Encoder

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2372
• Wer: 20.1528

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2134	0.37	500	0.2738	23.3480
0.1845	0.73	1000	0.2588	22.2679
0.1056	1.1	1500	0.2445	21.2688
0.1009	1.46	2000	0.2414	20.7152
0.0962	1.83	2500	0.2330	20.1222
0.0554	2.19	3000	0.2388	20.5230
0.0578	2.56	3500	0.2388	20.3253
0.0512	2.92	4000	0.2372	20.1528

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2