---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Fake-Citation-Detector-V2-scibert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Fake-Citation-Detector-V2-scibert

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8244
- Accuracy: 0.6205
- Macro F1: 0.6028

## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 51
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.7055        | 1.0   | 86   | 0.6790          | 0.5723   | 0.5499   |
| 0.6908        | 2.0   | 172  | 0.6773          | 0.5723   | 0.5195   |
| 0.6122        | 3.0   | 258  | 0.6426          | 0.6325   | 0.6133   |
| 0.5333        | 4.0   | 344  | 0.6915          | 0.6205   | 0.5983   |
| 0.3916        | 5.0   | 430  | 0.7555          | 0.6205   | 0.6006   |
| 0.2788        | 6.0   | 516  | 0.8244          | 0.6205   | 0.6028   |


### Framework versions

- Transformers 5.17.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.2