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---
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
|