sentence_classfication_test

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

• Loss: 0.7145
• Accuracy: 0.7692

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	33	0.7357	0.6385
No log	2.0	66	0.6801	0.6615
No log	3.0	99	0.6015	0.7923
No log	4.0	132	0.6450	0.7615
No log	5.0	165	0.7437	0.7
No log	6.0	198	0.5748	0.7692
No log	7.0	231	0.8001	0.7077
No log	8.0	264	0.6965	0.7615
No log	9.0	297	0.7052	0.7538
No log	10.0	330	0.7145	0.7692

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3