---
base_model: Kevinger/setfit-hub-report
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Hub-Repoop-1706130115
  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. -->

# Hub-Repoop-1706130115

This model is a fine-tuned version of [Kevinger/setfit-hub-report](https://huggingface.co/Kevinger/setfit-hub-report) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1746
- F1: 0.7727
- Roc Auc: 0.8666
- Accuracy: 0.7637

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 13

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 277  | 0.3104          | 0.0    | 0.5     | 0.0      |
| 0.3599        | 2.0   | 554  | 0.2312          | 0.5624 | 0.7027  | 0.4135   |
| 0.3599        | 3.0   | 831  | 0.1897          | 0.7479 | 0.8275  | 0.6730   |
| 0.2035        | 4.0   | 1108 | 0.1768          | 0.7645 | 0.8546  | 0.7363   |
| 0.2035        | 5.0   | 1385 | 0.1760          | 0.7649 | 0.8579  | 0.7447   |
| 0.1422        | 6.0   | 1662 | 0.1788          | 0.7559 | 0.8562  | 0.7447   |
| 0.1422        | 7.0   | 1939 | 0.1766          | 0.7633 | 0.8617  | 0.7553   |
| 0.1096        | 8.0   | 2216 | 0.1746          | 0.7727 | 0.8666  | 0.7637   |
| 0.1096        | 9.0   | 2493 | 0.1891          | 0.7457 | 0.8511  | 0.7363   |
| 0.0891        | 10.0  | 2770 | 0.1855          | 0.7524 | 0.8540  | 0.7405   |
| 0.0769        | 11.0  | 3047 | 0.1824          | 0.7655 | 0.8629  | 0.7574   |
| 0.0769        | 12.0  | 3324 | 0.1835          | 0.7655 | 0.8629  | 0.7532   |
| 0.0706        | 13.0  | 3601 | 0.1867          | 0.7604 | 0.8603  | 0.7511   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1