DATASET02-fine-tuned

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: 0.9451

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: 0.0005
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	9	1.1077
No log	2.0	18	0.9729
No log	2.7033	24	0.9451

Framework versions

• PEFT 0.14.0
• Transformers 4.50.0.dev0
• Pytorch 2.5.1+cu121
• Datasets 3.3.2
• Tokenizers 0.21.0