bert-base-portuguese-fine-tuned-mrpc

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the glue-ptpt dataset. It achieves the following results on the evaluation set:

• Loss: 1.2843
• Accuracy: 0.8505
• F1: 0.8920

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	459	0.6757	0.8603	0.8966
0.2011	2.0	918	0.7120	0.8505	0.8897
0.1215	3.0	1377	0.9679	0.8382	0.8764
0.0901	4.0	1836	1.0548	0.8333	0.8799
0.0478	5.0	2295	1.3125	0.8260	0.8769
0.0312	6.0	2754	1.0122	0.8578	0.8953
0.0309	7.0	3213	1.2197	0.8431	0.8849
0.0095	8.0	3672	1.1705	0.8554	0.8941
0.0076	9.0	4131	1.3132	0.8480	0.8912
0.0014	10.0	4590	1.2843	0.8505	0.8920

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3