---
license: apache-2.0
base_model: sentence-transformers/all-mpnet-base-v2
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-finetuned-sem_eval-english
  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. -->

# bert-finetuned-sem_eval-english

This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5309
- F1: 0.6500
- Roc Auc: 0.7191
- Accuracy: 0.3001

## 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: 2e-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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.5324        | 1.0   | 9913  | 0.5302          | 0.6542 | 0.7212  | 0.2941   |
| 0.5068        | 2.0   | 19826 | 0.5309          | 0.6500 | 0.7191  | 0.3001   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2