deberta-v3-large__sst2__train-8-3

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: 0.6421
• Accuracy: 0.6310

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
0.6696	1.0	3	0.7917	0.25
0.6436	2.0	6	0.8107	0.25
0.6923	3.0	9	0.8302	0.25
0.5051	4.0	12	0.9828	0.25
0.3688	5.0	15	0.7402	0.25
0.2671	6.0	18	0.5820	0.75
0.1935	7.0	21	0.8356	0.5
0.0815	8.0	24	1.0431	0.25
0.0591	9.0	27	0.9679	0.75
0.0276	10.0	30	1.0659	0.75
0.0175	11.0	33	0.9689	0.75
0.0152	12.0	36	0.8820	0.75
0.006	13.0	39	0.8337	0.75
0.0041	14.0	42	0.7650	0.75
0.0036	15.0	45	0.6960	0.75
0.0034	16.0	48	0.6548	0.75

Framework versions

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