---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
datasets:
- scicite
metrics:
- accuracy
model-index:
- name: cite_classification
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: scicite
      type: scicite
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9170305676855895
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cite_classification

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6533
- Accuracy: 0.9170

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4909        | 1.0   | 719  | 0.2266          | 0.9181   |
| 0.3215        | 2.0   | 1438 | 0.3707          | 0.9181   |
| 0.0825        | 3.0   | 2157 | 0.5539          | 0.9159   |
| 0.0539        | 4.0   | 2876 | 0.5117          | 0.9159   |
| 0.0245        | 5.0   | 3595 | 0.5720          | 0.9094   |
| 0.0209        | 6.0   | 4314 | 0.5710          | 0.9170   |
| 0.0104        | 7.0   | 5033 | 0.6443          | 0.9116   |
| 0.0059        | 8.0   | 5752 | 0.6533          | 0.9170   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1