deberta-v3-large__sst2__train-8-2

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6794
• Accuracy: 0.6063

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6942	1.0	3	0.7940	0.25
0.6068	2.0	6	0.9326	0.25
0.6553	3.0	9	0.7979	0.25
0.475	4.0	12	0.7775	0.25
0.377	5.0	15	0.7477	0.25
0.3176	6.0	18	0.6856	0.75
0.2708	7.0	21	0.6554	0.75
0.2855	8.0	24	0.8129	0.5
0.148	9.0	27	0.7074	0.75
0.0947	10.0	30	0.7090	0.75
0.049	11.0	33	0.7885	0.75
0.0252	12.0	36	0.9203	0.75
0.0165	13.0	39	1.0937	0.75
0.0084	14.0	42	1.2502	0.75
0.0059	15.0	45	1.3726	0.75
0.0037	16.0	48	1.4784	0.75
0.003	17.0	51	1.5615	0.75

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.2+cu102
• Datasets 1.18.2
• Tokenizers 0.10.3