hBERTv1_new_pretrain_48_KD_stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48_KD on the GLUE STSB dataset. It achieves the following results on the evaluation set:

• Loss: 1.9753
• Pearson: 0.4441
• Spearmanr: 0.4350
• Combined Score: 0.4395

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
2.2736	1.0	45	2.5807	0.1213	0.1131	0.1172
1.9996	2.0	90	2.3578	0.1791	0.1901	0.1846
1.7489	3.0	135	2.1912	0.2981	0.2958	0.2970
1.4124	4.0	180	2.8188	0.2915	0.2901	0.2908
1.1148	5.0	225	2.3077	0.3345	0.3206	0.3276
0.8203	6.0	270	2.4569	0.3944	0.3852	0.3898
0.6562	7.0	315	2.1797	0.4086	0.4082	0.4084
0.5537	8.0	360	2.2254	0.4198	0.4180	0.4189
0.5236	9.0	405	2.2477	0.4231	0.4100	0.4166
0.3807	10.0	450	2.1156	0.4398	0.4346	0.4372
0.3645	11.0	495	1.9753	0.4441	0.4350	0.4395
0.2975	12.0	540	2.3133	0.4634	0.4537	0.4585
0.2781	13.0	585	2.3479	0.4473	0.4469	0.4471
0.2308	14.0	630	2.2469	0.4441	0.4376	0.4408
0.2555	15.0	675	2.0949	0.4840	0.4772	0.4806
0.2003	16.0	720	2.0903	0.4814	0.4742	0.4778

Framework versions

• Transformers 4.30.2
• Pytorch 1.14.0a0+410ce96
• Datasets 2.12.0
• Tokenizers 0.13.3