text_classifier

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: 3.2472
• Accuracy: 0.6158

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.4863	1.0	760	2.0973	0.2474
1.8132	2.0	1520	1.7995	0.4237
1.5143	3.0	2280	1.5842	0.5053
1.3095	4.0	3040	1.8946	0.5553
1.0743	5.0	3800	1.9189	0.5684
0.9554	6.0	4560	2.1748	0.5974
0.7778	7.0	5320	2.2701	0.6263
0.5849	8.0	6080	2.5282	0.6237
0.5472	9.0	6840	2.7330	0.6184
0.4232	10.0	7600	2.9518	0.6079
0.2858	11.0	8360	2.8892	0.6263
0.2908	12.0	9120	3.0251	0.6289
0.2391	13.0	9880	3.1414	0.6211
0.1569	14.0	10640	3.2581	0.6184
0.1405	15.0	11400	3.2472	0.6158

Framework versions

• Transformers 4.36.0
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0