distilbert-base-uncased-enneagram

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: 2.0632
• Accuracy: 0.625
• F1: 0.55

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: 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	F1
No log	1.0	1	2.2359	0.25	0.1562
No log	2.0	2	2.2038	0.25	0.1562
No log	3.0	3	2.1745	0.25	0.1562
No log	4.0	4	2.1484	0.375	0.2857
No log	5.0	5	2.1260	0.5	0.4167
No log	6.0	6	2.1058	0.5	0.4167
No log	7.0	7	2.0888	0.625	0.55
2.1836	8.0	8	2.0762	0.625	0.55
2.1836	9.0	9	2.0678	0.625	0.55
2.1836	10.0	10	2.0632	0.625	0.55

Framework versions

• Transformers 4.30.0
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.13.3