Kwimp/whisper-small_TLT_Finetuned_no_augment

whisper small finetuned TLT non-native child speech

This model is a fine-tuned version of openai/whisper-small on the LTL2021 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4034
• Wer: 18.5163

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: 32
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• 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: 2048
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.0933	1.7857	500	2.9951	17.7932
3.1499	3.5714	1000	1.8692	16.9543
1.7621	5.3571	1500	1.0117	17.4699
0.7934	7.1429	2000	0.4569	19.5452
0.7021	8.9286	2500	0.4180	18.7828
0.6198	10.7143	3000	0.4087	19.0821
0.5799	12.5	3500	0.4047	19.8991
0.5980	14.2857	4000	0.4034	18.5163

Framework versions

• Transformers 5.8.1
• Pytorch 2.5.1+cu121
• Datasets 4.8.5
• Tokenizers 0.22.2