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Model: selimc/OrpoGemma-2-9B-TR
Source: Original Platform

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README.md

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+---
+library_name: transformers
+tags:
+- Turkish
+- TR
+- ORPO
+datasets:
+- selimc/orpo-dpo-mix-TR-20k
+language:
+- tr
+base_model:
+- google/gemma-2-9b-it
+license: gemma
+
+model-index:
+- name: OrpoGemma-2-9B-TR
+  results:
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: MMLU_TR_V0.2
+      metrics:
+      - name: 5-shot
+        type: 5-shot
+        value: 0.530
+        verified: false
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: Truthful_QA_V0.2
+      metrics:
+      - name: 0-shot
+        type: 0-shot
+        value: 0.543
+        verified: false
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: ARC_TR_V0.2
+      metrics:
+      - name: 25-shot
+        type: 25-shot
+        value: 0.524
+        verified: false
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: HellaSwag_TR_V0.2
+      metrics:
+      - name: 10-shot
+        type: 10-shot
+        value: 0.520
+        verified: false
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: GSM8K_TR_V0.2
+      metrics:
+      - name: 5-shot
+        type: 5-shot
+        value: 0.648
+        verified: false
+    - task:
+        type: multiple-choice
+      dataset:
+        type: multiple-choice
+        name: Winogrande_TR_V0.2
+      metrics:
+      - name: 5-shot
+        type: 5-shot
+        value: 0.589
+        verified: false
+---
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65281302cad797fc4abeffd7/Hqf7vdvp6dudVjN_bLKU_.png)
+
+# OrpoGemma-2-9B-TR
+
+OrpoGemma-2-9B-TR is a Turkish fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it). It is trained using the ORPO Trainer on a subset of 1500 rows from the dataset [selimc/orpo-dpo-mix-TR-20k](https://huggingface.co/datasets/selimc/orpo-dpo-mix-tr-20k).
+
+## Training Information
+
+- **Base Model**: [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
+- **Fine-Tuning Technique**: ORPO
+- **Training Data**: 1500 rows from [selimc/orpo-dpo-mix-TR-20k](https://huggingface.co/datasets/selimc/orpo-dpo-mix-tr-20k)
+- **Training Time**: 2.5 hours on NVIDIA H100
+
+  ### QLoRA Configurations:
+    - `lora_r`: 16
+    - `lora_alpha`: 32
+    - `lora_dropout`: 0.05
+  
+  ### ORPO Training Parameters
+    - `lr`: 2e-6
+    - `epochs`: 3
+    - `per_device_train_batch_size`: 8
+    - `gradient_accumulation_steps`: 4
+
+## 📈 Training Curves
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65281302cad797fc4abeffd7/bdhWq-TbvQ-h_aSQDf2pv.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65281302cad797fc4abeffd7/mKdVsAjBdsmMMhXorKVoV.png)
+
+## OpenLLMTurkishLeaderboard_v0.2 Results
+
+| Dataset               | Score  |
+|-----------------------|--------|
+| MMLU_TR_V0.2         | 53.0%  |
+| Truthful_QA_TR_V0.2  | 54.3%  |
+| ARC_TR_V0.2          | 52.4%  |
+| HellaSwag_TR_V0.2    | 52.0%  |
+| GSM8K_TR_V0.2        | 64.8%  |
+| Winogrande_TR_V0.2   | 58.9%  |
+| **Average**          | **55.9%** |
+
+Thanks to the [WiroAI](https://huggingface.co/WiroAI) team for evaluating my model. Evaluations were done without any inference engine.
+
+## Model Capabilities
+
+- Produces fluent, coherent, and contextually appropriate text in Turkish.
+- Delivers detailed and informative responses to a wide range of instructions and question types.
+- May still produce incorrect or nonsensical outputs, user verification is recommended.
+
+## How to Use
+
+```python
+from transformers import pipeline, BitsAndBytesConfig, AutoTokenizer
+import torch
+
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16
+)
+
+model_id = "selimc/OrpoGemma-2-9B-TR"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+pipe = pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16 ,'quantization_config': bnb_config},
+    tokenizer=tokenizer,
+    device_map="auto"
+)
+
+messages = [
+    {"role": "user", "content": "Gökyüzü neden mavi?"},
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+outputs = pipe(
+    prompt,
+    max_new_tokens=512,
+    do_sample=True,
+    eos_token_id=[pipe.tokenizer.convert_tokens_to_ids("<end_of_turn>"), pipe.tokenizer.eos_token_id],
+    temperature=0.67,
+)
+
+generated_text = outputs[0]['generated_text']
+response = generated_text[len(prompt):]
+print(response)
+```
+
+### Example 1
+
+```python
+messages = [
+    {"role": "user", "content": """Bir web sayfasından tüm URL’leri çeken bir Python fonksiyonu yazın ve nasıl çalıştığını açıklayın."""},
+]
+```
+
+``````
+Bir web sayfasından tüm URL’leri çeken bir Python fonksiyonu yazalım ve nasıl çalıştığını açıklayalım.
+
+```python
+import requests
+
+def get_urls_from_page(url):
+  """
+  
+  Bir web sayfasından tüm URL'leri çeker.
+
+  Args:
+      url (str): Web sayfasının URL'i.
+
+  Returns:
+      list: Web sayfasındaki tüm URL'ler.
+  """
+  response = requests.get(url)
+  response.raise_for_status()
+
+  urls = []
+  for link in response.html.find_all('a', href=True):
+    urls.append(link['href'])
+
+  return urls
+
+# Örnek kullanım
+
+web_page_url = 'https://www.example.com/'
+all_urls = get_urls_from_page(web_page_url)
+print(f"Bu web sayfasındaki {len(all_urls)} URL bulunmaktadır:\n{all_urls}")
+```
+
+**Fonksiyonun nasıl çalıştığı:**
+
+1. **`requests` kütüphanesini içer:** Bu kütüphane web sayfalarına erişmek için kullanılır.
+2. **`get_urls_from_page` fonksiyonunu tanımla:** 
+   * Bu fonksiyon, bir web sayfasının URL'ini alır.
+   * `requests.get()` kullanarak web sayfasına erişir ve `response.raise_for_status()` kullanarak HTTP durum kodunun 200-399 aralığında olup olmadığını kontrol eder.
+   * `response.html` içine bir HTML belgesini saklar.
+   * `response.html.find_all('a', href=True)` kullanarak, `href` atributuna sahip tüm `<a>` etiketlerini bulur. 
+   * `urls` listesine URL'leri ekler.
+   * `urls` listesini döndürür.
+
+3. **Örnek kullanım:**
+
+   * `web_page_url` değişkenine bir web sayfasının URL'ini atar.
+   * `get_urls_from_page` fonksiyonunu kullanarak web sayfasından tüm URL'leri çeker.
+   * `all_urls` listesini `print()` fonksiyonu kullanarak ekrana yazdır
+
+``````
+
+### Example 2
+
+```python
+messages = [
+    {
+        "role": "system",
+        "content":
+          """
+          Sen bir türkçe bilmece ustasısın. Görevin:
+            - Sorulan bilmecelere mantıklı ve doğru cevaplar vermek
+            - Bilmecenin çözümünü adım adım açıklamak
+          """
+    },
+    {
+        "role": "user",
+        "content":
+          """
+            Kanadı var, kuş değil.
+            Suda yüzer, gemi değil.
+            Kuyruğu var, kedi değil.
+            Bil bakalım, bu nedir?
+          """
+    },
+]
+```
+
+```
+Kanadı var, kuş değil, suda yüzer, gemi değil, kuyruğu var, kedi değil... Bu bir **balık**! 🐟
+```
+
+## Citation
+
+```bibtex
+@misc{orpogemma2-9b-tr,
+  author = {Selim Çavaş},
+  title = {OrpoGemma-2-9B-TR: Turkish Fine-tuned Gemma Model},
+  year = {2024},
+  url = {https://huggingface.co/selimc/OrpoGemma-2-9B-TR}
+}
+```

config.json

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+{
+  "_name_or_path": "google/gemma-2-9b-it",
+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": 50.0,
+  "bos_token_id": 256000,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 256001,
+  "final_logit_softcapping": 30.0,
+  "head_dim": 256,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 42,
+  "num_key_value_heads": 8,
+  "pad_token_id": 256001,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "sliding_window_size": 4096,
+  "torch_dtype": "float16",
+  "transformers_version": "4.46.3",
+  "use_cache": true,
+  "vocab_size": 256002
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 256000,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 256001,
+  "pad_token_id": 256001,
+  "transformers_version": "4.46.3"
+}

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