xlsr53-ptbr-cv-final3

This model is a fine-tuned version of lejonck/xlsr53-ptbr-cv-final2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4771
• Wer: 0.2904
• Cer: 0.1026

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: 2
• eval_batch_size: 2
• 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: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.1101	1.0	1500	0.4152	0.3063	0.1059
0.0819	2.0	3000	0.4207	0.2969	0.1047
0.1629	3.0	4500	0.4262	0.3057	0.1073
0.0972	4.0	6000	0.4369	0.2992	0.1044
0.0653	5.0	7500	0.4398	0.2928	0.1015
0.0325	6.0	9000	0.4839	0.3034	0.1067
0.0285	7.0	10500	0.4771	0.2904	0.1026
0.0749	8.0	12000	0.4734	0.2928	0.1029
0.1061	9.0	13500	0.4737	0.2922	0.1009
0.1082	10.0	15000	0.4749	0.2928	0.1034
0.0434	11.0	16500	0.4708	0.2910	0.1028
0.081	12.0	18000	0.4675	0.2904	0.1022

Framework versions

• Transformers 4.55.1
• Pytorch 2.7.0+cu126
• Datasets 2.19.1
• Tokenizers 0.21.4