---
license: apache-2.0
base_model: michiyasunaga/BioLinkBERT-large
tags:
- generated_from_trainer
datasets:
- scicite
metrics:
- accuracy
model-index:
- name: cite_classification_model
  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: 0.925764192139738
---

<!-- 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. -->

# cite_classification_model

This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the scicite dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4804
- Accuracy: 0.9258

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2679        | 1.0   | 513  | 0.1976          | 0.9258   |
| 0.1903        | 2.0   | 1026 | 0.2146          | 0.9225   |
| 0.1474        | 3.0   | 1539 | 0.2356          | 0.9225   |
| 0.1105        | 4.0   | 2052 | 0.3363          | 0.9279   |
| 0.0785        | 5.0   | 2565 | 0.3935          | 0.9225   |
| 0.0498        | 6.0   | 3078 | 0.4296          | 0.9236   |
| 0.0293        | 7.0   | 3591 | 0.4774          | 0.9203   |
| 0.0186        | 8.0   | 4104 | 0.4804          | 0.9258   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0