pos_test_model_1

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: 0.1521
• Accuracy: 0.9530
• F1: 0.9523
• Precision: 0.9576
• Recall: 0.9530

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.1882	1.0	1744	0.1521	0.9530	0.9523	0.9576	0.9530

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.2
• Datasets 2.2.2
• Tokenizers 0.12.1