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HONGBANJANG1/
DATASET02-fine-tuned

Name: DATASET02-fine-tuned
Availability: InStock

peft

safetensors

generated_from_trainer

LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct

adapter

other

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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

HONGBANJANG1/DATASET02-fine-tuned

DATASET02-fine-tuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

HONGBANJANG1/
DATASET02-fine-tuned