roberta-base-finetuned-sts

This model is a fine-tuned version of klue/roberta-base on the klue dataset. It achieves the following results on the evaluation set:

• Loss: 0.1999
• Pearsonr: 0.9560

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: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 200
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Pearsonr
No log	1.0	329	0.2462	0.9478
1.2505	2.0	658	0.1671	0.9530
1.2505	3.0	987	0.1890	0.9525
0.133	4.0	1316	0.2360	0.9548
0.0886	5.0	1645	0.2265	0.9528
0.0886	6.0	1974	0.2097	0.9518
0.0687	7.0	2303	0.2281	0.9523
0.0539	8.0	2632	0.2212	0.9542
0.0539	9.0	2961	0.1843	0.9532
0.045	10.0	3290	0.1999	0.9560
0.0378	11.0	3619	0.2357	0.9533
0.0378	12.0	3948	0.2134	0.9541
0.033	13.0	4277	0.2273	0.9540
0.03	14.0	4606	0.2148	0.9533
0.03	15.0	4935	0.2207	0.9534

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6