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

Loss: 0.2154
Wer: 0.1442

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
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 16
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 5000
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3915	0.47	1000	0.2978	0.1858
0.2942	0.93	2000	0.2500	0.1626
0.2877	1.4	3000	0.2336	0.1536
0.2303	1.87	4000	0.2225	0.1482
0.2192	2.33	5000	0.2154	0.1442

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.2.1
Datasets 2.16.1
Tokenizers 0.15.2

fsicoli/whisper-small-pt-cv16-fleurs

whisper-small-pt-cv16-fleurs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fsicoli/
whisper-small-pt-cv16-fleurs