ryota39
/

Gakki-7B-reward-v0.1

@@ -3,197 +3,98 @@ library_name: transformers
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 tags: []
 ---
+## Fine-tuning model
+- metric shows as blow
+- F1 score shows around 0.70.
+- Major reason arises from low quality of dataset
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/651e3f30ca333f3c8df692b8/sxAgjKrxSIyJ6V95Yg3Ne.png)
+## Model Training
+- Fine-tuning on [open preference-v0.2](https://huggingface.co/datasets/ryota39/open_preference_v0.2)
+## Model Merge
+Gakki-7B was build by [Chat Vector](https://arxiv.org/abs/2310.04799)
+A recipe shows as below
+```
+Rakuten/RakutenAI-7B-instruct + (prometheus-eval/prometheus-7b-v2.0 - mistralai/Mistral-7B-Instruct-v0.2)
+```
+## Source Code
+```python
+import torch
+from transformers import AutoModelForCausalLM
+def build_chat_vector_model(
+    base_model_name,
+    inst_model_name,
+    target_model_name,
+    skip_layers,
+    ):
+    base_model = AutoModelForCausalLM.from_pretrained(
+        base_model_name,
+        torch_dtype=torch.bfloat16,
+        device_map="cpu",
+    )
+    inst_model = AutoModelForCausalLM.from_pretrained(
+        inst_model_name,
+        torch_dtype=torch.bfloat16,
+        device_map="cpu",
+    )
+    target_model = AutoModelForCausalLM.from_pretrained(
+        target_model_name,
+        torch_dtype=torch.bfloat16,
+        device_map="cuda",
+    )
+    # 英語ベースモデル
+    for k, v in base_model.state_dict().items():
+        print(k, v.shape)
+    # 日本語継続事前学習モデル
+    for k, v in target_model.state_dict().items():
+        print(k, v.shape)
+    # 除外対象
+    skip_layers = ["model.embed_tokens.weight", "lm_head.weight"]
+    for k, v in target_model.state_dict().items():
+        # layernormも除外
+        if (k in skip_layers) or ("layernorm" in k):
+            continue
+        chat_vector = inst_model.state_dict()[k] - base_model.state_dict()[k]
+        new_v = v + chat_vector.to(v.device)
+        v.copy_(new_v)
+    target_model.save_pretrained("./Gakki-7B")
+    return
+if __name__ == '__main__':
+    base_model_name = "mistralai/Mistral-7B-Instruct-v0.2"
+    inst_model_name = "prometheus-eval/prometheus-7b-v2.0"
+    target_model_name = "Rakuten/RakutenAI-7B-instruct"
+    skip_layers = ["model.embed_tokens.weight", "lm_head.weight"]
+    build_chat_vector_model(
+        base_model_name=base_model_name,
+        inst_model_name=inst_model_name,
+        target_model_name=target_model_name,
+        skip_layers=skip_layers
+    )
+```