---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: citation_intent_classification_roberta
  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. -->

# citation_intent_classification_roberta

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9427
- Accuracy: 0.7986
- F1 Macro: 0.6913

## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.4059        | 1.0   | 105  | 1.0585          | 0.6491   | 0.2714   |
| 1.0405        | 2.0   | 211  | 0.9258          | 0.6842   | 0.3254   |
| 0.8144        | 3.0   | 316  | 0.7686          | 0.7281   | 0.4907   |
| 0.5887        | 4.0   | 422  | 0.7906          | 0.7456   | 0.5518   |
| 0.404         | 5.0   | 527  | 0.6946          | 0.7719   | 0.7045   |
| 0.3302        | 6.0   | 633  | 0.8840          | 0.7719   | 0.6330   |
| 0.225         | 7.0   | 738  | 0.8200          | 0.8070   | 0.7258   |
| 0.1843        | 8.0   | 844  | 0.8336          | 0.8070   | 0.7533   |
| 0.16          | 9.0   | 949  | 0.8221          | 0.8246   | 0.7641   |
| 0.0977        | 9.95  | 1050 | 0.8798          | 0.8246   | 0.7649   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.13.1+cu117
- Datasets 2.13.2
- Tokenizers 0.13.3