deberta-v3-xsmall-Label_B-1024-epoch-4

This model is a fine-tuned version of microsoft/deberta-v3-xsmall on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1110
• Accuracy: 0.9786
• F1: 0.9786
• Precision: 0.9791
• Recall: 0.9786

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: 5e-05
• train_batch_size: 10
• eval_batch_size: 10
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 40
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0987	0.9994	1279	0.1147	0.9656	0.9654	0.9671	0.9656
0.0393	1.9996	2559	0.0855	0.9786	0.9786	0.9791	0.9786
0.0217	2.9998	3839	0.1205	0.9759	0.9760	0.9769	0.9759
0.0011	3.9977	5116	0.1110	0.9786	0.9786	0.9791	0.9786

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0