pogny-32-0.00002

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

• Loss: 1.7335
• Accuracy: 0.7654
• F1: 0.7631

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1015	1.0	2409	1.3422	0.7540	0.7527
0.0623	2.0	4818	1.5917	0.7656	0.7616
0.0317	3.0	7227	1.7335	0.7654	0.7631

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0a0+b5021ba
• Datasets 2.6.2
• Tokenizers 0.14.1