update model card README.md

README.md

@@ -1,48 +1,66 @@
 ---
-license: cc-by-sa-4.0
-datasets:
-- kubota/defamation-japanese-twitter
-language:
-- ja
-pipeline_tag: text-classification
-widget:
-- text: お前のことを殺すぞ
-- text: 本当に不細工だなぁ
-- text: あの人は殺人を犯した犯罪者らしい
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: luke-large-defamation-detection-japanese
+  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-large-defamation-detection-japanese
-# 日本語誹謗中傷検出器
 
-This model is a fine-tuned version of [studio-ousia/luke-japanese-large](https://huggingface.co/studio-ousia/luke-japanese-large) for the Japanese language finetuned for automatic defamation detection. 
+This model is a fine-tuned version of [studio-ousia/luke-japanese-large](https://huggingface.co/studio-ousia/luke-japanese-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4430
+- Accuracy: 0.6616
+- F1: 0.6381
+- Auc: 0.8630
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
 
-The original foundation model was finetuned on a balanced dataset created by unifying two datasets:
-- [![Generic badge](https://img.shields.io/badge/Dataset-DefamationJapaneseTwitter-red.svg)](https://huggingface.co/datasets/kubota/defamation-japanese-twitter) 
-- `DefamationJapaneseYouTube` : TBA 
+### Training hyperparameters
 
-<b>Labels</b>:\
-0 -> "中傷性のない発言"\
-1 -> "脅迫的な発言"\
-2 -> "侮蔑的な発言"\
-3"-> "名誉を低下させる発言"
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 777
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 4
+- mixed_precision_training: Native AMP
 
-## Example Pipeline
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/kubotaissei/defamation_japanese_twitter/blob/master/notebooks/pipeline_example.ipynb)
-```python
-# !pip install transformers==4.26 sentencepiece
-from transformers import pipeline
-pipe = pipeline(model="kubota/luke-large-defamation-detection-japanese")
-pipe("あの人は殺人を犯した犯罪者らしい")
-```
-```
-[{'label': '名誉を低下させる発言', 'score': 0.8889994621276855}]
-```
-## Training Scripts
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/kubotaissei/defamation_japanese_twitter/blob/master/notebooks/train_example.ipynb)
+### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
+| 0.4219        | 1.0   | 1780 | 0.3979          | 0.6630   | 0.6084 | 0.8466 |
+| 0.3375        | 2.0   | 3560 | 0.4050          | 0.6706   | 0.6242 | 0.8618 |
+| 0.2716        | 3.0   | 5340 | 0.4362          | 0.6595   | 0.6370 | 0.8626 |
+| 0.2331        | 4.0   | 7120 | 0.4430          | 0.6616   | 0.6381 | 0.8630 |
 
-## Licenses
 
-The finetuned model with all attached files is licensed under [CC BY-SA 4.0](http://creativecommons.org/licenses/by-sa/4.0/), or Creative Commons Attribution-ShareAlike 4.0 International License. 
+### Framework versions
 
-<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a>
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu116
+- Datasets 2.8.0
+- Tokenizers 0.13.2