gigazine-title-classification

This model is a fine-tuned version of tohoku-nlp/bert-base-japanese on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4894
• Accuracy: 0.617

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: 8
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 256
• 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
0.5588	0.768	3	1.5196	0.602
0.3835	1.792	7	1.4909	0.61
0.2563	2.304	9	1.4894	0.617

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1