distillbert-base-sst-myers-briggs-classifier

This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 4
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
2.022	1.0	868	1.9076
1.9125	2.0	1736	1.5352
1.6338	3.0	2604	1.1828
1.2065	4.0	3472	0.7410
0.6499	5.0	4340	0.4132
0.4899	6.0	5208	0.3122
0.3508	7.0	6076	0.1947
0.2563	8.0	6944	0.1733
0.0166	9.0	7812	0.0869
0.0048	10.0	8680	0.0697
0.0598	11.0	9548	0.0246
0.0491	12.0	10416	0.0236
0.1285	13.0	11284	0.0147
0.0373	14.0	12152	0.0034
0.0003	15.0	13020	0.0000
0.0002	16.0	13888	0.0001
0.0038	17.0	14756	0.0000
0.0004	18.0	15624	0.0000
0.0	19.0	16492	0.0000
0.0	20.0	17360	0.0000

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.20.3