Update README.md

README.md

@@ -1,75 +1,56 @@
----
-library_name: transformers
-license: mit
-base_model: distilbert-base-uncased
-tags:
-- question-answering
-- distilbert
-- squad
-- fine-tuning
-datasets:
-- squad
-metrics:
-- loss
-- exact_match
-- f1
-model-index:
-- name: my_awesome_qa_model
-  results:
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: SQuAD v1.1
-      type: squad
-      split: validation
-    metrics:
-    - name: Exact Match
-      type: exact_match
-      value: 请在此填写您的 EM 分数
-    - name: F1 Score
-      type: f1
-      value: 请在此填写您的 F1 分数
----
+---
+library_name: transformers
+license: mit
+base_model: distilbert-base-uncased
+tags:
+- question-answering
+- distilbert
+- squad
+- fine-tuning
+datasets:
+- squad
+model-index:
+- name: my_awesome_qa_model
+  results:
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: SQuAD v1.1
+      type: squad
+      split: validation
+    metrics:
+    - name: Exact Match
+      type: exact_match
+      value: Please fill in your EM score
+    - name: F1 Score
+      type: f1
+      value: Please fill in your F1 score
+language:
+- en
+---
 
 # my_awesome_qa_model
 
-本模型是 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) 的微调版本，针对 [SQuAD v1.1 数据集](https://huggingface.co/datasets/squad) 进行了训练。
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased), trained on the [SQuAD v1.1 dataset](https://huggingface.co/datasets/squad).
 
-它在验证集上取得了以下结果：
+It achieved the following results on the validation set:
 
-- **Loss（损失）**: 1.7489
+- **Loss**: 1.7489
 
-## 模型描述
-
-该模型基于 DistilBERT，是 BERT 的精简版本，参数更少，速度更快，但性能仍接近原始 BERT。通过在 SQuAD 数据集上微调，模型学习了从给定的上下文中抽取回答问题的能力。
-
-## 预期用途与限制
-
-### 预期用途
-
-- **问答系统**：适用于需要从文本中抽取答案的应用，如聊天机器人、信息检索等。
-- **教育目的**：演示如何微调预训练模型以执行特定任务。
-
-### 限制
-
-- **语言局限**：模型仅在英文数据上进行训练，对其他语言的支持可能有限。
-- **知识截止**：模型的知识截止于其训练数据，无法理解训练后发生的事件。
-- **领域适应性**：在特定领域（如医学、法律）可能表现不佳，需要在相关领域数据上进一步微调。
-
-## 使用方法
+## How to Use
 
 ```python
 from transformers import pipeline
 
-# 加载模型
+# Load the model
 question_answerer = pipeline(
     "question-answering",
     model="real-jiakai/my_awesome_qa_model",
     tokenizer="real-jiakai/my_awesome_qa_model"
 )
 
-# 英文示例
+# English example
 context_en = """
 Donald Trump was the 45th president of the United States, serving from 2017 to 2021.
 """
@@ -80,22 +61,20 @@ result_en = question_answerer(question=question_en, context=context_en)
 print("Answer:", result_en['answer'])
 ```
 
-## 许可证
+## License
 
-本模型采用 MIT 许可证。
+This model is licensed under the [MIT](https://opensource.org/license/mit) License.
 
-## 引用
+## Citation
 
-如果您在您的工作中使用了本模型，请引用：
+If you use this model in your work, please cite:
 
 ```
-@misc{real-jiakai2024awesome,
-  author       = {Real-Jiakai},
-  title        = {My Awesome QA Model},
+@misc{my_awesome_qa_model,
+  author       = {real-jiakai},
+  title        = {my_awesome_qa_model},
   year         = {2024},
-  publisher    = {Hugging Face},
-  howpublished = {Hugging Face Model Repository},
   url          = {https://huggingface.co/real-jiakai/my_awesome_qa_model},
-  note         = {Accessed: YYYY-MM-DD}
+  publisher    = {Hugging Face}
 }
 ```