---
license: apache-2.0
base_model: studio-ousia/luke-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: luke-base
  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-base

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: 0.3638
- Accuracy: 0.8492
- Precision: 0.8536
- Recall: 0.8429
- F1: 0.8482

## 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=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4523        | 1.0   | 1074 | 0.4276          | 0.8191   | 0.8383    | 0.7908 | 0.8139 |
| 0.3397        | 2.0   | 2148 | 0.3576          | 0.8472   | 0.8528    | 0.8393 | 0.8460 |
| 0.2865        | 3.0   | 3222 | 0.3638          | 0.8492   | 0.8536    | 0.8429 | 0.8482 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0