distilbert-base-uncased-operator

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

• Loss: 0.0145
• Accuracy: 0.9832
• Precision: 0.9847
• Recall: 0.9813
• F1: 0.9830

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.0323	1.0	15979	0.0207	0.9779	0.9756	0.9799	0.9778
0.0138	2.0	31958	0.0145	0.9832	0.9847	0.9813	0.9830

Framework versions

• Transformers 4.34.0
• Pytorch 2.1.0+cu118
• Tokenizers 0.14.1