This model is a fine-tuned version of KJnr/finetuned-whisper-small-V1.0.0 on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.4920
Wer: 53.5032

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: 5e-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 8
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: linear
lr_scheduler_warmup_ratio: 0.05
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.268	0.3333	1000	0.5192	69.2031
0.2296	0.6667	2000	0.5010	49.9377
0.2441	1.0	3000	0.4920	53.5032

Framework versions

Transformers 4.52.4
Pytorch 2.5.1+cu124
Datasets 3.6.0
Tokenizers 0.21.0

KJnr/whisper-small-mult-2xt-continued

whisper-small-mult-2xt-continued

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

KJnr/
whisper-small-mult-2xt-continued