hBERTv2_new_pretrain_48_stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

• Loss: 2.0734
• Pearson: 0.4184
• Spearmanr: 0.4028
• Combined Score: 0.4106

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: 4e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 10
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Pearson	Spearmanr	Combined Score
2.2864	1.0	45	3.0157	0.1270	0.1171	0.1220
1.9895	2.0	90	2.7270	0.1553	0.1550	0.1552
1.7101	3.0	135	2.8223	0.2806	0.2657	0.2732
1.2973	4.0	180	2.5938	0.3375	0.3280	0.3328
1.0658	5.0	225	2.3835	0.3771	0.3629	0.3700
0.8454	6.0	270	2.5028	0.3637	0.3479	0.3558
0.6773	7.0	315	2.3937	0.3594	0.3538	0.3566
0.5678	8.0	360	2.6813	0.3803	0.3802	0.3803
0.4746	9.0	405	2.5546	0.3874	0.3695	0.3784
0.4113	10.0	450	2.2077	0.4112	0.4038	0.4075
0.3585	11.0	495	2.2846	0.4096	0.3972	0.4034
0.3288	12.0	540	2.4155	0.4012	0.3848	0.3930
0.2745	13.0	585	2.3635	0.4004	0.3924	0.3964
0.2579	14.0	630	2.0734	0.4184	0.4028	0.4106
0.2309	15.0	675	2.3462	0.4171	0.4026	0.4099
0.2037	16.0	720	2.2598	0.4225	0.4090	0.4157
0.1806	17.0	765	2.2458	0.4116	0.3916	0.4016
0.1785	18.0	810	2.3296	0.4088	0.3903	0.3996
0.1582	19.0	855	2.3369	0.4033	0.3868	0.3951

Framework versions

• Transformers 4.29.2
• Pytorch 1.14.0a0+410ce96
• Datasets 2.12.0
• Tokenizers 0.13.3