roberta-large_MBTI_N_MBTI_agg_balanced_100

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 3.5612
• F1: 0.6361
• Threshold: 0.28
• F1 At 05: 0.6289

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 64
• total_eval_batch_size: 64
• optimizer: Use OptimizerNames.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: 400
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Threshold	F1 At 05
2.1302	0.3876	200	2.8632	0.5228	0.5700	0.5071
2.0681	0.7752	400	2.6842	0.5753	0.4300	0.5665
1.8350	1.1628	600	2.4720	0.5981	0.47	0.5970
1.6722	1.5504	800	2.4994	0.6147	0.54	0.6131
1.6335	1.9380	1000	2.3575	0.6186	0.51	0.6161
1.3358	2.3256	1200	2.7270	0.6226	0.5	0.6226
1.3158	2.7132	1400	2.4540	0.6451	0.17	0.5992
0.9204	3.1008	1600	2.9904	0.6367	0.49	0.6341
0.8488	3.4884	1800	3.1322	0.6369	0.2400	0.6325
0.9459	3.8760	2000	3.1577	0.6336	0.48	0.6325
0.5991	4.2636	2200	3.9174	0.6258	0.48	0.6233
0.6461	4.6512	2400	3.5612	0.6361	0.28	0.6289

Framework versions

• Transformers 5.3.0
• Pytorch 2.7.1
• Datasets 4.8.5
• Tokenizers 0.22.2