update

app.py

@@ -300,13 +300,23 @@ if __name__ == "__main__":
     MODE_REL_SINGLE = "Relative (By Dataset)"
     lc_modes = [MODE_ABS_AVG, MODE_ABS_SINGLE, MODE_REL_AVG, MODE_REL_SINGLE]
     default_lc_mode = MODE_ABS_AVG
+    # init_lc_choices = lc_dm.get_model_choices(default_lc_period)
     init_lc_choices = lc_dm.get_model_choices(default_lc_period)
     print(init_lc_choices)
 
+    def get_default_model(choices):
+        """获取默认模型，优先选择 Qwen3-8B-Base，否则返回第一个模型"""
+        if not choices:
+            return None
+        for display_name, model_name in choices:
+            if model_name == "Qwen3-8B-Base":
+                return model_name
+        return choices[0][1]
+
     def create_initial_lc_plot():
         if not init_lc_choices:
             return None
-        default_model = init_lc_choices[0][1]
+        default_model = get_default_model(init_lc_choices)
         data_map = {}
         paths = lc_dm.get_paths_for_model(default_lc_period, default_model)
         data_map[default_model] = paths
@@ -378,7 +388,8 @@ if __name__ == "__main__":
 
                         gr.Markdown("### Model / Dataset Selection")
 
-                        default_selected_models = [init_lc_choices[0][1]] if init_lc_choices else []
+                        default_model = get_default_model(init_lc_choices)
+                        default_selected_models = [default_model] if default_model else []
                         lc_select_abs = gr.Dropdown(
                             label="Select Models", choices=init_lc_choices, value=default_selected_models, multiselect=True, visible=True
                         )
@@ -437,13 +448,25 @@ if __name__ == "__main__":
                     is_single_dataset = "By Dataset" in mode
                     is_relative = "Relative" in mode
 
+                    def get_default_model(choices):
+                        """获取默认模型，优先选择 Qwen3-8B-Base，否则返回第一个模型"""
+                        if not choices:
+                            return None
+                        for display_name, model_name in choices:
+                            if model_name == "Qwen3-8B-Base":
+                                return model_name
+                        return choices[0][1] if choices else None
+
                     if is_model_agg:
                         # Averaged by Model mode - use existing logic
                         choices = lc_dm.get_model_choices(period)
                         label_suffix = "Models"
                         if not is_relative:
+                            # Absolute (Averaged by Model) - 默认选择 Qwen3-8B-Base
+                            default_model = get_default_model(choices)
+                            default_selected = [default_model] if default_model else []
                             return (
-                                gr.update(visible=True, choices=choices, label=f"Select {label_suffix}", value=[]),
+                                gr.update(visible=True, choices=choices, label=f"Select {label_suffix}", value=default_selected),
                                 gr.update(visible=False, choices=choices, value=None),
                                 gr.update(visible=False, choices=choices, value=[]),
                                 gr.update(visible=False, value=[]),
@@ -452,9 +475,10 @@ if __name__ == "__main__":
                                 gr.update(visible=False, value=[]),
                             )
                         else:
+                            default_baseline = get_default_model(choices)
                             return (
                                 gr.update(visible=False, choices=choices, value=[]),
-                                gr.update(visible=True, choices=choices, label=f"Baseline", value=None),
+                                gr.update(visible=True, choices=choices, label=f"Baseline", value=default_baseline),
                                 gr.update(visible=True, choices=choices, label=f"Comparison", value=[]),
                                 gr.update(visible=False, value=[]),
                                 gr.update(visible=False, value=[]),
@@ -466,25 +490,28 @@ if __name__ == "__main__":
                         dataset_choices = lc_dm.get_dataset_choices(period)
                         model_choices = lc_dm.get_model_choices(period)
                         if not is_relative:
-                            # Absolute By Dataset
+                            # Absolute By Dataset - 默认选择 Qwen3-8B-Base
+                            default_model = get_default_model(model_choices)
+                            default_selected = [default_model] if default_model else []
                             return (
                                 gr.update(visible=False, value=[]),
                                 gr.update(visible=False, value=None),
                                 gr.update(visible=False, value=[]),
                                 gr.update(visible=True, choices=dataset_choices, value=[]),
-                                gr.update(visible=True, choices=model_choices, value=[]),
+                                gr.update(visible=True, choices=model_choices, value=default_selected),
                                 gr.update(visible=False, value=None),
                                 gr.update(visible=False, value=[]),
                             )
                         else:
                             # Relative By Dataset - use same datasets for all models
+                            default_baseline = get_default_model(model_choices)
                             return (
                                 gr.update(visible=False, value=[]),
                                 gr.update(visible=False, value=None),
                                 gr.update(visible=False, value=[]),
                                 gr.update(visible=True, choices=dataset_choices, value=[]),
                                 gr.update(visible=False, value=[]),
-                                gr.update(visible=True, choices=model_choices, value=None),
+                                gr.update(visible=True, choices=model_choices, value=default_baseline),
                                 gr.update(visible=True, choices=model_choices, value=[]),
                             )
 

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-ao3_english-2025-12-23_02-02-29.json

@@ -1,29 +0,0 @@
-{
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-    "avg tokens": 1833.526,
-    "avg character count": 7857.404,
-    "parameters count": 7.298617344,
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-    "sample_count": 500,
-    "model_name_or_path": "allenai/OLMo-2-1124-7B",
-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-ao3_english",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
-    "enable_chunking": true,
-    "bpc": 0.820909016047146,
-    "bpb": 0.8050448034800882,
-    "compression_rate": 10.063060043501103,
-    "track_byte_wise_data": false
-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-arxiv_cs-2025-12-23_02-03-16.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 4154.937625,
-    "avg tokens": 2049.684,
-    "avg character count": 9964.74,
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-    "model_name_or_path": "allenai/OLMo-2-1124-7B",
-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-arxiv_cs",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
-    "enable_chunking": true,
-    "bpc": 0.6015518625463853,
-    "bpb": 0.5997829832468091,
-    "compression_rate": 7.497287290585114,
-    "track_byte_wise_data": false
-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-arxiv_math-2025-12-23_02-04-23.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 3742.297125,
-    "avg tokens": 2984.626,
-    "avg character count": 9913.284,
-    "parameters count": 7.298617344,
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-    "model_name_or_path": "allenai/OLMo-2-1124-7B",
-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-arxiv_math",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
-    "enable_chunking": true,
-    "bpc": 0.5446220953389942,
-    "bpb": 0.5443261371197929,
-    "compression_rate": 6.804076713997412,
-    "track_byte_wise_data": false
-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-arxiv_physics-2025-12-23_02-05-19.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 4125.7,
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-arxiv_physics",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
-    "enable_chunking": true,
-    "bpc": 0.5983856929952361,
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-    "compression_rate": 7.475442752536468,
-    "track_byte_wise_data": false
-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-bbc_news-2025-12-23_02-05-39.json

@@ -1,29 +0,0 @@
-{
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-    "avg tokens": 709.082,
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-bbc_news",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
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-    "bpc": 0.6818005144559561,
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-    "track_byte_wise_data": false
-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-github_cpp-2025-12-23_02-06-17.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 1470.37925,
-    "avg tokens": 1598.048,
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-github_cpp",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
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-    "bpc": 0.3674324613699604,
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-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-github_javascript-2025-12-23_02-06-53.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 1559.5025,
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-github_javascript",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [],
-    "batch_size": 1,
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-    "bpc": 0.3896073361746562,
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-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-github_markdown-2025-12-23_02-07-29.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 2375.605625,
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-github_markdown",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
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-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-github_python-2025-12-23_02-08-07.json

@@ -1,29 +0,0 @@
-{
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-github_python",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
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-    "batch_size": 1,
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-}

data/2025-12/OLMo-2-1124-7B-UncheatableEval-2025-12-wikipedia_english-2025-12-23_02-08-28.json

@@ -1,29 +0,0 @@
-{
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-    "tokenizer_name": "allenai/OLMo-2-1124-7B",
-    "data_path": "UncheatableEval-2025-12-wikipedia_english",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true,
-        "attn_implementation": "flash_attention_2",
-        "torch_dtype": "torch.float16"
-    },
-    "tokenizer_args": {
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-}

data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-ao3_english-2025-12-23_01-53-27.json

@@ -1,29 +0,0 @@
-{
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-    "tokenizer_name": "rwkv_vocab_v20230424",
-    "data_path": "UncheatableEval-2025-12-ao3_english",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true
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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-arxiv_cs-2025-12-23_01-54-29.json

@@ -1,29 +0,0 @@
-{
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-    "tokenizer_name": "rwkv_vocab_v20230424",
-    "data_path": "UncheatableEval-2025-12-arxiv_cs",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true
-    },
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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-arxiv_math-2025-12-23_01-55-56.json

@@ -1,29 +0,0 @@
-{
-    "neg_log_prob_sum": 3883.796088394165,
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-    "tokenizer_name": "rwkv_vocab_v20230424",
-    "data_path": "UncheatableEval-2025-12-arxiv_math",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [
-        "rwkv"
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-}

data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-arxiv_physics-2025-12-23_01-57-08.json

@@ -1,29 +0,0 @@
-{
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-    "tokenizer_name": "rwkv_vocab_v20230424",
-    "data_path": "UncheatableEval-2025-12-arxiv_physics",
-    "chunk_size": 4000,
-    "ensure_bos_token": true,
-    "model_args": {
-        "device_map": "auto",
-        "trust_remote_code": true
-    },
-    "tokenizer_args": {
-        "trust_remote_code": true
-    },
-    "requirements": [
-        "rwkv"
-    ],
-    "batch_size": 1,
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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-bbc_news-2025-12-23_01-57-33.json

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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-github_cpp-2025-12-23_01-58-27.json

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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-github_javascript-2025-12-23_01-59-17.json

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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-github_markdown-2025-12-23_02-00-05.json

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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-github_python-2025-12-23_02-00-59.json

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data/2025-12/RWKV-5-World-7B-v2-20240128-ctx4096-UncheatableEval-2025-12-wikipedia_english-2025-12-23_02-01-23.json

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