---
license: apache-2.0
base_model: studio-ousia/luke-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: luke-paper-setup-multiple-choice
  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. -->

# luke-paper-setup-multiple-choice

This model is a fine-tuned version of [studio-ousia/luke-base](https://huggingface.co/studio-ousia/luke-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3685
- Accuracy: 0.8383
- Precision: 0.8472
- Recall: 0.8254
- F1: 0.8362

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.638         | 1.0   | 1074 | 0.4769          | 0.7764   | 0.7621    | 0.8036 | 0.7823 |
| 0.4198        | 2.0   | 2148 | 0.3650          | 0.8312   | 0.8380    | 0.8211 | 0.8295 |
| 0.3556        | 3.0   | 3222 | 0.3685          | 0.8383   | 0.8472    | 0.8254 | 0.8362 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0