This model is a fine-tuned version of openai/whisper-medium on the fsicoli/cv16-fleurs default dataset. It achieves the following results on the evaluation set:

Loss: 0.1428
Wer: 0.0949

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 25000
training_steps: 25000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2244	2.3343	5000	0.1728	0.1110
0.1471	4.6685	10000	0.1515	0.0996
0.149	7.0028	15000	0.1428	0.0949
0.0697	9.3371	20000	0.1436	0.0940
0.0374	11.6713	25000	0.1561	0.0972

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.1
Datasets 2.21.0
Tokenizers 0.19.1

fsicoli/whisper-medium-pt-cv16-fleurs2

whisper-medium-pt-cv16-fleurs2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fsicoli/
whisper-medium-pt-cv16-fleurs2