---
license: apache-2.0
base_model: sentence-transformers/paraphrase-mpnet-base-v2
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: paraphrase-mpnet-base-v2_mbti_full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# paraphrase-mpnet-base-v2_mbti_full

This model is a fine-tuned version of [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5933
- F1: 0.5931
- Roc Auc: 0.6834

## 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  | 0.5755          | 0.4804 | 0.6197  |
| 0.5774        | 2.0   | 651  | 0.5656          | 0.2262 | 0.5484  |
| 0.5774        | 3.0   | 976  | 0.5515          | 0.3992 | 0.6041  |
| 0.5594        | 4.0   | 1302 | 0.5487          | 0.4959 | 0.6344  |
| 0.5352        | 5.0   | 1627 | 0.5429          | 0.5776 | 0.6775  |
| 0.5352        | 6.0   | 1953 | 0.5557          | 0.5332 | 0.6560  |
| 0.4996        | 7.0   | 2278 | 0.5681          | 0.5895 | 0.6837  |
| 0.4531        | 8.0   | 2604 | 0.5793          | 0.5783 | 0.6783  |
| 0.4531        | 9.0   | 2929 | 0.5924          | 0.5982 | 0.6882  |
| 0.4204        | 9.98  | 3250 | 0.5970          | 0.5786 | 0.6778  |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2