deberta-v3-large__sst2__train-16-3

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: 0.6286
• Accuracy: 0.7068

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
0.6955	1.0	7	0.7370	0.2857
0.6919	2.0	14	0.6855	0.4286
0.6347	3.0	21	0.5872	0.7143
0.4016	4.0	28	0.6644	0.7143
0.3097	5.0	35	0.5120	0.7143
0.0785	6.0	42	0.5845	0.7143
0.024	7.0	49	0.6951	0.7143
0.0132	8.0	56	0.8972	0.7143
0.0037	9.0	63	1.5798	0.7143
0.0034	10.0	70	1.5178	0.7143
0.003	11.0	77	1.3511	0.7143
0.0012	12.0	84	1.1346	0.7143
0.0007	13.0	91	0.9752	0.7143
0.0008	14.0	98	0.8531	0.7143
0.0007	15.0	105	0.8149	0.7143

Framework versions

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