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

Loss: 0.0665
Wer: 7.8539

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: 64
eval_batch_size: 64
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: 100
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1775	0.2	200	0.1581	17.6588
0.3073	0.4	400	0.1794	20.2935
0.0724	1.133	600	0.0737	8.4709
0.2589	1.333	800	0.1090	14.3238
0.0379	2.066	1000	0.0665	7.8539

Framework versions

Transformers 4.52.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.4

sitwala/whisper-large-v3-turbo-nchlt-zul

Whisper whisper-large-v3-turbo nchlt

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sitwala/
whisper-large-v3-turbo-nchlt-zul