logs_rand

This model is a fine-tuned version of klue/roberta-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0024
• Precision: 0.8742
• Recall: 0.8871
• F1: 0.8806
• Accuracy: 0.9992

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: 64
• 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	Precision	Recall	F1	Accuracy
No log	1.0	57	0.0067	0.6685	0.6276	0.6474	0.9980
No log	2.0	114	0.0035	0.8286	0.8312	0.8299	0.9989
No log	3.0	171	0.0028	0.8690	0.8745	0.8717	0.9991
No log	4.0	228	0.0026	0.8693	0.8840	0.8766	0.9992
No log	5.0	285	0.0024	0.8742	0.8871	0.8806	0.9992

Framework versions

• Transformers 4.40.2
• Pytorch 2.0.1
• Datasets 2.19.1
• Tokenizers 0.19.1