RitroD
/

naver_review

Text Classification

Generated from Trainer

text-embeddings-inference

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naver_review

This model is a fine-tuned version of beomi/kcbert-base on the None dataset. It achieves the following results on the evaluation set:

eval_loss: 0.0867
eval_runtime: 176.2901
eval_samples_per_second: 283.606
eval_steps_per_second: 17.726
epoch: 1.0
step: 9375

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Downloads last month: 8

Safetensors

Model size

0.1B params

Tensor type

F32

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beomi/kcbert-base

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