This model is a fine-tuned version of openai/whisper-medium on the fsicoli/cv19-fleurs default dataset in Portuguese. It achieves the following results on the evaluation set:

Loss: 0.2108
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: 6.25e-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: 500
training_steps: 25000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0339	2.2883	5000	0.1694	0.1025
0.0281	4.5767	10000	0.1852	0.1005
0.0139	6.8650	15000	0.2092	0.1002
0.0044	9.1533	20000	0.2087	0.0960
0.0055	11.4416	25000	0.2108	0.0949

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.1
Datasets 2.21.0
Tokenizers 0.19.1

fsicoli/whisper-medium-pt-cv19-fleurs2-lr-wu

whisper-medium-pt-cv19-fleurs2-lr-wu

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fsicoli/
whisper-medium-pt-cv19-fleurs2-lr-wu