ops_subcate

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

• Loss: 0.1575
• Accuracy: 0.7428
• F1: 0.7647
• Precision: 0.7715
• Recall: 0.7581

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: 64
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	49	0.1300	0.7291	0.7604	0.7883	0.7345
No log	2.0	98	0.1272	0.7391	0.7707	0.7989	0.7444
No log	3.0	147	0.1294	0.7391	0.7654	0.7918	0.7407
No log	4.0	196	0.1388	0.7341	0.7567	0.7733	0.7407
No log	5.0	245	0.1326	0.7541	0.7791	0.8026	0.7568
No log	6.0	294	0.1407	0.7478	0.7743	0.7940	0.7556
No log	7.0	343	0.1445	0.7341	0.7576	0.7712	0.7444
No log	8.0	392	0.1533	0.7528	0.7684	0.7776	0.7593
No log	9.0	441	0.1573	0.7628	0.7747	0.7816	0.7680
No log	10.0	490	0.1575	0.7428	0.7647	0.7715	0.7581

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1