alikanakar/whisper-small-CV-43-llr

Whisper Small Tr - CV 43h - LLR

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: 0.2477
• Wer: 21.3892

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-06
• 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
0.2468	0.37	500	0.2886	24.3238
0.2099	0.73	1000	0.2673	22.8161
0.1841	1.1	1500	0.2577	22.0433
0.1767	1.46	2000	0.2540	21.8600
0.1718	1.83	2500	0.2504	21.6444
0.1629	2.19	3000	0.2492	21.6120
0.1693	2.56	3500	0.2486	21.4161
0.1594	2.92	4000	0.2477	21.3892

Framework versions

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