DeBERTaV3_model_V5

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: 0.1164
• Accuracy: 0.9652
• F1: 0.8192
• Precision: 0.8524
• Recall: 0.7885

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: 5
• eval_batch_size: 5
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	182	0.2809	0.9	0.0	0.0	0.0
No log	2.0	364	0.2176	0.9216	0.4027	0.8451	0.2643
0.2842	3.0	546	0.1558	0.9493	0.7074	0.8373	0.6123
0.2842	4.0	728	0.1302	0.9568	0.7742	0.8116	0.7401
0.2842	5.0	910	0.1164	0.9652	0.8192	0.8524	0.7885
0.1025	6.0	1092	0.1193	0.9634	0.8135	0.8303	0.7974
0.1025	7.0	1274	0.1242	0.9648	0.8214	0.8326	0.8106
0.1025	8.0	1456	0.1266	0.9626	0.8098	0.8227	0.7974
0.0376	9.0	1638	0.1259	0.9648	0.8206	0.8356	0.8062
0.0376	10.0	1820	0.1269	0.9661	0.8285	0.8378	0.8194
0.023	11.0	2002	0.1290	0.9661	0.8293	0.8348	0.8238
0.023	12.0	2184	0.1312	0.9630	0.8150	0.8150	0.8150

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.1+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1