bert_base_cased_MultiClass_v2

This model is a fine-tuned version of HMEXBI/bert_base_cased_MultiClass on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9806
• Accuracy: 0.8101

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: 8
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1396	1.0	545	0.9023	0.7615
0.6961	2.0	1090	0.8074	0.7798
0.492	3.0	1635	0.8216	0.8009
0.3032	4.0	2180	0.9264	0.8018
0.1898	5.0	2725	0.9806	0.8101

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.0
• Tokenizers 0.13.2