repo_id = "x2bee/ModernBERT-ecs-GIST-category"

model_file = hf_hub_download(repo_id=repo_id, filename="model.py", token=token)
spec = importlib.util.spec_from_file_location("MajorClassifier", model_file)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
MajorClassifier = module.MajorClassifier

clf_model = MajorClassifier(repo_id)

# use
text = '반팔티셔츠'
clf_model(text)

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 16
total_train_batch_size: 4096
total_eval_batch_size: 256
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_ratio: 0.1
num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss
2.0282	1.0845	1000	0.1349

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0