deberta-myers-briggs-classifier

This model is a fine-tuned version of microsoft/deberta-base 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
1.6415	1.0	868	1.7265
1.6881	2.0	1736	1.3475
1.5645	3.0	2604	1.0214
1.0915	4.0	3472	0.7177
0.6687	5.0	4340	0.4303
0.4507	6.0	5208	0.3196
0.5139	7.0	6076	0.1659
0.5381	8.0	6944	0.1550
0.2482	9.0	7812	0.0851
0.0942	10.0	8680	0.0824
0.1959	11.0	9548	0.0536
0.0547	12.0	10416	0.0248
0.0049	13.0	11284	0.0127
0.0451	14.0	12152	0.0096
0.0001	15.0	13020	0.0091
0.0	16.0	13888	0.0085
0.0	17.0	14756	0.0000
0.0	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