This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on the klue-ynat dataset.
It achieves the following results on the evaluation set:
eval_loss: 2.0522
eval_accuracy: 0.0917
eval_precision: 0.0131
eval_recall: 0.1429
eval_f1: 0.0240
eval_runtime: 14.6861
eval_samples_per_second: 620.111
eval_steps_per_second: 38.812
epoch: 1.0
step: 2855
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
