---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: my_awesome_model
  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. -->

# misdirection_classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.6937
- Precision: 0.6959
- Recall: 0.6937
- F1: 0.6829
- Roc Auc: 0.6835

## 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: 4.890081827045594e-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: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.6496        | 1.0   | 28   | 0.6713          | 0.6216   | 0.6683    | 0.6216 | 0.5502 | 0.6567  |
| 0.4718        | 2.0   | 56   | 0.7125          | 0.6486   | 0.6463    | 0.6486 | 0.6348 | 0.6667  |
| 0.2081        | 3.0   | 84   | 0.9041          | 0.6937   | 0.6959    | 0.6937 | 0.6829 | 0.6835  |
| 0.1064        | 4.0   | 112  | 1.1360          | 0.6667   | 0.6720    | 0.6667 | 0.6474 | 0.6928  |
| 0.0202        | 5.0   | 140  | 1.1922          | 0.6577   | 0.6543    | 0.6577 | 0.6540 | 0.6928  |
| 0.1239        | 6.0   | 168  | 1.4047          | 0.6667   | 0.6690    | 0.6667 | 0.6506 | 0.6753  |
| 0.074         | 7.0   | 196  | 1.3902          | 0.6486   | 0.6448    | 0.6486 | 0.6441 | 0.6683  |
| 0.0738        | 8.0   | 224  | 1.4045          | 0.6486   | 0.6478    | 0.6486 | 0.6482 | 0.6650  |
| 0.0458        | 9.0   | 252  | 1.4082          | 0.6306   | 0.6316    | 0.6306 | 0.6311 | 0.6634  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1