plateer_classifier_exaone_test

This model is a fine-tuned version of LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 3.4783
• Accuracy: 0.1333

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: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10000
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Framework versions

• PEFT 0.13.2
• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 2.19.0
• Tokenizers 0.20.3