llm-selector

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: 1.7315
• Accuracy: 0.5048

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: 8
• eval_batch_size: 8
• 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	118	1.8920	0.3714
No log	2.0	236	1.7753	0.5143
No log	3.0	354	1.7671	0.4952
No log	4.0	472	1.7441	0.5048
1.8665	5.0	590	1.7315	0.5048
1.8665	6.0	708	1.7413	0.5048
1.8665	7.0	826	1.7378	0.4667
1.8665	8.0	944	1.7426	0.4667
1.7254	9.0	1062	1.7513	0.4476
1.7254	10.0	1180	1.7513	0.4476

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1
• Datasets 2.12.0
• Tokenizers 0.13.3