update README.md

README.md

@@ -1,3 +1,58 @@
 ---
 license: other
+datasets:
+- taishi-i/awesome-japanese-nlp-classification-dataset
+language:
+- en
+- ja
+metrics:
+- f1
+library_name: transformers
+pipeline_tag: text-classification
 ---
+
+# Model overview
+
+This model is the baseline model for [awesome-japanese-nlp-classification-dataset](https://huggingface.co/datasets/taishi-i/awesome-japanese-nlp-classification-dataset). It was trained on this dataset, saved using the development data, and evaluated using the test data. The following table shows the evaluation results.
+
+| Label        | Precision | Recall | F1-Score | Support |
+|--------------|-----------|--------|----------|---------|
+| 0            | 0.98      | 0.99   | 0.98     | 796     |
+| 1            | 0.79      | 0.70   | **0.74** | 60      |
+| Accuracy     |           |        | 0.97     | 856     |
+| Macro Avg    | 0.89      | 0.84   | 0.86     | 856     |
+| Weighted Avg | 0.96      | 0.97   | 0.97     | 856     |
+
+
+# Usage
+
+Please install the following library.
+
+```bash
+pip install transformers
+```
+
+You can easily use a classification model with the pipeline method.
+
+```python
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-classification",
+    model="taishi-i/awesome-japanese-nlp-classification-model",
+)
+
+# Relevant sample
+text = "ディープラーニングによる自然言語処理（共立出版）のサポートページです"
+label = pipe(text)
+print(label) # [{'label': '1', 'score': 0.9910495281219482}]
+
+# Not Relevant sample
+text = "AIイラストを管理するデスクトップアプリ"
+label = pipe(text)
+print(label) # [{'label': '0', 'score': 0.9986791014671326}]
+```
+
+# License
+
+This model was trained from a dataset collected from the GitHub API under [GitHub Acceptable Use Policies - 7. Information Usage Restrictions](https://docs.github.com/en/site-policy/acceptable-use-policies/github-acceptable-use-policies#7-information-usage-restrictions) and [GitHub Terms of Service - H. API Terms](https://docs.github.com/en/site-policy/github-terms/github-terms-of-service#h-api-terms). It should be used solely for research verification purposes. Adhering to GitHub's regulations is mandatory.