ModernBERT-ecs-GIST-category
This model is a fine-tuned version of x2bee/ModernBERT-ecs-GIST-ckp01 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1349
Model description
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 = '๋ฐํํฐ์
์ธ '
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
- Downloads last month
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Model tree for x2bee/ModernBERT-ecs-GIST-category
Base model
x2bee/ModernBERT-ecs-GIST-ckp01