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README.md

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----
-license: mit
----
+---
+license: mit
+---
+
+**Base model:** [westlake-repl/SaProt_650M_AF2](https://huggingface.co/westlake-repl/SaProt_650M_AF2)
+
+**Dataset:** This dataset contains 100K randomly generated mutants derived from the wild type EYFP protein. The number of samples for 
+training, validation and test is 100317, 5969 and 5968. 10% of double-site mutants and 10% of triple-site mutants were used for validation and test 
+respectively, and the remains for training. This model was trained by Jia Zheng's lab at Westlake University. The dataset will be released later by this team.
+
+**Performance (on test set):** 0.94 Spearman's ρ
+
+**LoRA config:**
+- **r:** 8
+- **lora_dropout:** 0.0
+- **lora_alpha:** 16
+- **target_modules:** ["query", "key", "value", "intermediate.dense", "output.dense"]
+- **modules_to_save:** ["classifier"]
+
+**Training config:**
+
+- **optimizer:**
+  - **class:** AdamW
+  - **betas:** (0.9, 0.98)
+  - **weight_decay:** 0.01
+- **learning rate:** 1e-4
+- **epoch:** 20
+- **batch size:** 64
+- **precision:** 16-mixed

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/sujin/Models/SaProt/SaProt_650M_AF2",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier"
+  ],
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "value",
+    "key",
+    "output.dense",
+    "intermediate.dense",
+    "query"
+  ],
+  "task_type": "SEQ_CLS",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:74c5dd376ee3552f3fd9d57094cc15ae10182569f5a1d8471e03a6e4b5aa37ae
+size 15502914

metadata.json

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+{
+  "training_data_type": "AA"
+}