whisper-tiny-as-LDCIL-sentenceAligned_ChotaTesting

This model is a fine-tuned version of openai/whisper-tiny on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.3640
• Wer: 125.9777

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
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 20
• training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.4	20	1.8993	156.5992
2.2744	0.8	40	1.5240	183.4846
1.5738	1.2	60	1.4388	129.3296
1.432	1.6	80	1.3968	137.8142
1.364	2.0	100	1.3640	125.9777

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3