This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2281
Accuracy: 0.9286

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: 64
eval_batch_size: 64
seed: 42
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
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4929	5.0	20	0.4759	0.8929
0.1498	10.0	40	0.2220	0.8929
0.0244	15.0	60	0.1492	0.9286
0.0103	20.0	80	0.1755	0.9286
0.0069	25.0	100	0.2381	0.9286
0.0052	30.0	120	0.1952	0.9286
0.0047	35.0	140	0.2168	0.9286
0.004	40.0	160	0.2249	0.9286
0.004	45.0	180	0.2260	0.9286
0.0038	50.0	200	0.2281	0.9286

Framework versions

Transformers 4.57.1
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.22.1

53gf4u1t/XCommentsClassificationModel

XCommentsClassificationModel

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

53gf4u1t/
XCommentsClassificationModel