This model is a fine-tuned version of sentence-transformers/nli-mpnet-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5768
F1: 0.4807
Roc Auc: 0.6200

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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc
No log	1.0	325	0.5771	0.4804	0.6197
0.5798	2.0	651	0.5766	0.0	0.5
0.5798	3.0	976	0.5764	0.0	0.5
0.576	4.0	1302	0.5760	0.0	0.5
0.5762	5.0	1627	0.5762	0.0	0.5
0.5762	6.0	1953	0.5760	0.0	0.5
0.5762	7.0	2278	0.5761	0.4804	0.6197
0.5741	8.0	2604	0.5759	0.4804	0.6197
0.5741	9.0	2929	0.5759	0.4804	0.6197
0.5769	9.98	3250	0.5760	0.4804	0.6197

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

ClaudiaRichard/nli-mpnet-base-v2_mbti_full

nli-mpnet-base-v2_mbti_full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ClaudiaRichard/
nli-mpnet-base-v2_mbti_full