bert-base-uncased-mrpc-lora-epochs-10-lr-0.0005

This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 1.1795
• Accuracy: 0.8
• F1: 0.8611

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: 0.0005
• train_batch_size: 32
• eval_batch_size: 32
• seed: 28
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	112	0.5047	0.76	0.8333
No log	2.0	224	0.4400	0.78	0.8358
No log	3.0	336	0.5103	0.78	0.8406
No log	4.0	448	0.6321	0.78	0.8382
0.3586	5.0	560	0.8909	0.73	0.8
0.3586	6.0	672	0.8763	0.77	0.8369
0.3586	7.0	784	1.0331	0.8	0.8571
0.3586	8.0	896	1.1871	0.8	0.8611
0.0479	9.0	1008	1.1310	0.79	0.8552
0.0479	10.0	1120	1.1795	0.8	0.8611

Framework versions

• Transformers 4.32.0.dev0
• Pytorch 2.0.1
• Datasets 2.14.4
• Tokenizers 0.13.3