Create README.md

README.md

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+---
+license: mit
+datasets:
+- ZeynepAltundal/w
+language:
+- tr
+base_model:
+- ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- Turkish
+- Fine-tuned
+- Question-Answering
+- GPT-2
+---
+# Model Overview:
+This model is a fine-tuned version of the "ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1", designed specifically for Turkish Question-Answering (Q&A). The fine-tuning process utilized a custom dataset generated from Turkish Wikipedia articles, focusing on factual knowledge.
+
+**Base Model:** ytu-ce-cosmos/turkish-gpt2-medium-350m-instruct-v0.1
+**Fine-Tuned Dataset:** Custom Turkish Q&A dataset
+**Evaluation Loss:** 2.1461 (on the validation dataset)
+
+
+## Quick Start
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+
+model_name = "./fine_tuned_model"  # Replace with your Hugging Face model path if uploaded
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+
+question = "Kamu sosyolojisi nedir?"
+
+
+input_ids = tokenizer(question, return_tensors="pt").input_ids
+
+
+output = model.generate(
+    input_ids=input_ids,
+    max_length=50,
+    num_return_sequences=1,
+    temperature=0.7
+)
+
+response = tokenizer.decode(output[0], skip_special_tokens=True)
+print(f"Question: {question}")
+print(f"Answer: {response}")
+```
+
+## Training Details:
+**Dataset Source:** Custom dataset generated from Turkish Wikipedia
+**Number of Training Examples:** 2,606
+**Training Dataset Size:** 2,084 (80%)
+**Validation Dataset Size:** 522 (20%)
+**Number of Epochs:** 3
+**Batch Size:** 8
+**Learning Rate:** 5e-5
+**Evaluation Loss:** 2.1461