Merge evals
Browse files- app.py +15 -3
- debug.ipynb +458 -110
app.py
CHANGED
@@ -11,7 +11,7 @@ Evaluation of H4 and community models across a diverse range of benchmarks from
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"""
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-
def get_leaderboard_df():
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filepaths = list(Path("eval_results").rglob("*.json"))
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# Parse filepaths to get unique models
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@@ -66,11 +66,17 @@ def get_leaderboard_df():
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df = df.reset_index().rename(columns={"index": "Model"}).round(2)
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# Strip off date from model name
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df["Model"] = df["Model"].apply(lambda x: x.rsplit("_", 1)[0])
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return df
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-
def refresh():
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return get_leaderboard_df()
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# Function to update the table based on search query
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@@ -94,11 +100,17 @@ with demo:
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gr.Markdown(DESCRIPTION, elem_classes="markdown-text")
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with gr.Row():
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search_bar = gr.Textbox(placeholder="Search for your model...", show_label=False)
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with gr.Group():
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leaderboard_table = gr.Dataframe(value=leaderboard_df, wrap=True, height=1000)
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with gr.Row():
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refresh_button = gr.Button("Refresh")
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search_bar.submit(update_table, inputs=[search_bar], outputs=[leaderboard_table])
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refresh_button.click(refresh, inputs=[], outputs=[leaderboard_table])
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"""
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+
def get_leaderboard_df(merge_values: bool = False):
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filepaths = list(Path("eval_results").rglob("*.json"))
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# Parse filepaths to get unique models
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df = df.reset_index().rename(columns={"index": "Model"}).round(2)
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# Strip off date from model name
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df["Model"] = df["Model"].apply(lambda x: x.rsplit("_", 1)[0])
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if merge_values:
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merged_df = df.drop(["Date", "Average"], axis=1).groupby("Model").max().reset_index()
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merged_df.insert(loc=0, column="Average", value=merged_df.mean(axis=1, numeric_only=True))
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merged_df = merged_df.sort_values(by=["Average"], ascending=False).round(2)
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df = df[["Model", "Date"]].merge(merged_df, on="Model", how="left")
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return df
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def refresh(merge_values: bool = False):
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return get_leaderboard_df(merge_values)
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# Function to update the table based on search query
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gr.Markdown(DESCRIPTION, elem_classes="markdown-text")
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with gr.Row():
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search_bar = gr.Textbox(placeholder="Search for your model...", show_label=False)
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merge_values = gr.Checkbox(
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label="Merge evals",
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info="Merge evals for the same model. If there are duplicates, we display the largest one.",
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)
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with gr.Group():
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leaderboard_df = get_leaderboard_df()
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leaderboard_table = gr.Dataframe(value=leaderboard_df, wrap=True, height=1000)
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with gr.Row():
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refresh_button = gr.Button("Refresh")
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merge_values.change(refresh, inputs=[merge_values], outputs=[leaderboard_table])
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search_bar.submit(update_table, inputs=[search_bar], outputs=[leaderboard_table])
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refresh_button.click(refresh, inputs=[], outputs=[leaderboard_table])
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debug.ipynb
CHANGED
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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" data = json.load(file)\n",
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" first_result_key = next(iter(data[\"results\"])) # gets the first key in 'results'\n",
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" # TruthfulQA has two metrics, so we need to pick the `mc2` one that's reported on the leaderboard\n",
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" if task == \"truthfulqa\":\n",
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" value = data[\"results\"][first_result_key][\"truthfulqa_mc2\"]\n",
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" else:\n",
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" first_metric_key = next(
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" value = data[\"results\"][first_result_key][first_metric_key] # gets the value of the first metric\n",
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" df.loc[model_revision, task] = value\n",
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-
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" # Drop rows where every entry is NaN\n",
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" df = df.dropna(how=\"all\", axis=0, subset=[c for c in df.columns if c != \"Date\"])\n",
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" df.insert(loc=1, column=\"Average\", value=df.mean(axis=1, numeric_only=True))\n",
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" df = df.sort_values(by=[\"Average\"], ascending=False)\n",
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-
" df = df.reset_index().rename(columns={\"index\": \"Model\"}).round(
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" # Strip off date from model name\n",
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" df[\"Model\"] = df[\"Model\"].apply(lambda x: x.rsplit(\"_\", 1)[0])\n",
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" return df"
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -72,7 +88,7 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [
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{
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@@ -111,68 +127,68 @@
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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-
" <td>NousResearch_Nous-Hermes-2-
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-
" <td>2024-03-
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-
" <td>
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-
" <td>
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" <td>
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" <td>
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" <td>
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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-
" <td>
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-
" <td>2024-03-
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" <td>
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" <td>NaN</td>\n",
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-
" <td>
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" <td>
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" <td>NaN</td>\n",
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" <td>0.48</td>\n",
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" <td>0.640</td>\n",
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" <td>0.654</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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-
" <td>
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" <td>2024-03-02</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>2024-03-
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>deepseek-ai_deepseek-llm-67b-chat_main</td>\n",
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" <td>2024-03-
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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-
" <td>0.761</td>\n",
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" <td>0.42</td>\n",
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" <td>0.654</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <th>269</th>\n",
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" <td>HuggingFaceH4_starcoder2-15b-ift_v18.0</td>\n",
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" <td>2024-03-10</td>\n",
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-
" <td>
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>0.
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <th>270</th>\n",
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" <td>HuggingFaceH4_mistral-7b-ift_v49.0</td>\n",
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" <td>2024-03-07</td>\n",
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" <td>
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>0.
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <th>271</th>\n",
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" <td>HuggingFaceH4_starchat-beta_main</td>\n",
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" <td>2024-03-12</td>\n",
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" <td>
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <th>272</th>\n",
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" <td>HuggingFaceH4_starcoder2-15b-ift_v7.0</td>\n",
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" <td>2024-03-10</td>\n",
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-
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <th>273</th>\n",
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" <td>HuggingFaceH4_zephyr-7b-beta-ift_v1.1</td>\n",
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" <td>2024-03-13</td>\n",
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-
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>0.
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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],
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"text/plain": [
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" Model Date Average \\\n",
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-
"0
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-
"1
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-
"2
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"3
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"4 deepseek-ai_deepseek-llm-67b-chat_main 2024-03-
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".. ... ... ... \n",
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-
"269 HuggingFaceH4_starcoder2-15b-ift_v18.0 2024-03-10
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"270 HuggingFaceH4_mistral-7b-ift_v49.0 2024-03-07
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"271 HuggingFaceH4_starchat-beta_main 2024-03-12
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"272 HuggingFaceH4_starcoder2-15b-ift_v7.0 2024-03-10
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"273 HuggingFaceH4_zephyr-7b-beta-ift_v1.1 2024-03-13
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"\n",
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-
" Ifeval Truthfulqa Winogrande Gsm8k
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"\n",
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"[274 rows x 10 columns]"
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]
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},
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"execution_count":
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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{
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Model</th>\n",
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" <th>Average</th>\n",
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" <th>Ifeval</th>\n",
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" <th>Truthfulqa</th>\n",
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" <th>Winogrande</th>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <td>NaN</td>\n",
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|
|
|
|
|
|
|
|
355 |
" <td>NaN</td>\n",
|
356 |
" <td>NaN</td>\n",
|
|
|
357 |
" <td>NaN</td>\n",
|
358 |
" <td>NaN</td>\n",
|
359 |
" <td>NaN</td>\n",
|
360 |
" </tr>\n",
|
361 |
" </tbody>\n",
|
362 |
"</table>\n",
|
|
|
363 |
"</div>"
|
364 |
],
|
365 |
"text/plain": [
|
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-
"
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-
"
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-
"
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|
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"\n",
|
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-
"
|
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-
"50 0.359 0.672 0.453 0.33 0.656 0.545 \n",
|
372 |
-
"532 NaN NaN NaN NaN NaN NaN "
|
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]
|
374 |
},
|
375 |
-
"execution_count":
|
376 |
"metadata": {},
|
377 |
"output_type": "execute_result"
|
378 |
}
|
379 |
],
|
380 |
"source": [
|
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-
"df[
|
382 |
]
|
383 |
},
|
384 |
{
|
|
|
2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
+
"execution_count": 2,
|
6 |
"metadata": {},
|
7 |
"outputs": [],
|
8 |
"source": [
|
|
|
15 |
},
|
16 |
{
|
17 |
"cell_type": "code",
|
18 |
+
"execution_count": 3,
|
19 |
"metadata": {},
|
20 |
"outputs": [],
|
21 |
"source": [
|
|
|
44 |
" data = json.load(file)\n",
|
45 |
" first_result_key = next(iter(data[\"results\"])) # gets the first key in 'results'\n",
|
46 |
" # TruthfulQA has two metrics, so we need to pick the `mc2` one that's reported on the leaderboard\n",
|
47 |
+
" if task.lower() == \"truthfulqa\":\n",
|
48 |
" value = data[\"results\"][first_result_key][\"truthfulqa_mc2\"]\n",
|
49 |
+
" # IFEval has several metrics but we report just the prompt-loose-acc one\n",
|
50 |
+
" elif task.lower() == \"ifeval\":\n",
|
51 |
+
" value = data[\"results\"][first_result_key][\"prompt_level_loose_acc\"]\n",
|
52 |
+
" # MMLU has several metrics but we report just the average one\n",
|
53 |
+
" elif task.lower() == \"mmlu\":\n",
|
54 |
+
" value = data[\"results\"][\"lighteval|mmlu:_average|5\"][\"acc\"]\n",
|
55 |
+
" # HellaSwag and ARC reports acc_norm\n",
|
56 |
+
" elif task.lower() in [\"hellaswag\", \"arc\"]:\n",
|
57 |
+
" value = data[\"results\"][first_result_key][\"acc_norm\"]\n",
|
58 |
" else:\n",
|
59 |
+
" first_metric_key = next(\n",
|
60 |
+
" iter(data[\"results\"][first_result_key])\n",
|
61 |
+
" ) # gets the first key in the first result\n",
|
62 |
" value = data[\"results\"][first_result_key][first_metric_key] # gets the value of the first metric\n",
|
63 |
" df.loc[model_revision, task] = value\n",
|
64 |
+
"\n",
|
65 |
+
" # Put IFEval in first column\n",
|
66 |
+
" ifeval_col = df.pop(\"Ifeval\")\n",
|
67 |
+
" df.insert(1, \"Ifeval\", ifeval_col)\n",
|
68 |
" # Drop rows where every entry is NaN\n",
|
69 |
" df = df.dropna(how=\"all\", axis=0, subset=[c for c in df.columns if c != \"Date\"])\n",
|
70 |
" df.insert(loc=1, column=\"Average\", value=df.mean(axis=1, numeric_only=True))\n",
|
71 |
+
" # Convert all values to percentage\n",
|
72 |
+
" df[df.select_dtypes(include=[\"number\"]).columns] *= 100.0\n",
|
73 |
" df = df.sort_values(by=[\"Average\"], ascending=False)\n",
|
74 |
+
" df = df.reset_index().rename(columns={\"index\": \"Model\"}).round(2)\n",
|
75 |
" # Strip off date from model name\n",
|
76 |
" df[\"Model\"] = df[\"Model\"].apply(lambda x: x.rsplit(\"_\", 1)[0])\n",
|
77 |
" return df"
|
|
|
79 |
},
|
80 |
{
|
81 |
"cell_type": "code",
|
82 |
+
"execution_count": 4,
|
83 |
"metadata": {},
|
84 |
"outputs": [],
|
85 |
"source": [
|
|
|
88 |
},
|
89 |
{
|
90 |
"cell_type": "code",
|
91 |
+
"execution_count": 5,
|
92 |
"metadata": {},
|
93 |
"outputs": [
|
94 |
{
|
|
|
127 |
" <tbody>\n",
|
128 |
" <tr>\n",
|
129 |
" <th>0</th>\n",
|
130 |
+
" <td>NousResearch_Nous-Hermes-2-Yi-34B_main</td>\n",
|
131 |
+
" <td>2024-03-04</td>\n",
|
132 |
+
" <td>74.01</td>\n",
|
133 |
+
" <td>NaN</td>\n",
|
134 |
+
" <td>61.44</td>\n",
|
135 |
+
" <td>80.58</td>\n",
|
136 |
+
" <td>NaN</td>\n",
|
137 |
+
" <td>76.24</td>\n",
|
138 |
+
" <td>83.79</td>\n",
|
139 |
+
" <td>68.00</td>\n",
|
140 |
" </tr>\n",
|
141 |
" <tr>\n",
|
142 |
" <th>1</th>\n",
|
143 |
+
" <td>deepseek-ai_deepseek-llm-67b-chat_main</td>\n",
|
144 |
+
" <td>2024-03-05</td>\n",
|
145 |
+
" <td>71.62</td>\n",
|
146 |
+
" <td>55.27</td>\n",
|
147 |
+
" <td>NaN</td>\n",
|
148 |
" <td>NaN</td>\n",
|
149 |
+
" <td>76.12</td>\n",
|
150 |
+
" <td>71.18</td>\n",
|
151 |
+
" <td>83.94</td>\n",
|
152 |
" <td>NaN</td>\n",
|
|
|
|
|
|
|
153 |
" </tr>\n",
|
154 |
" <tr>\n",
|
155 |
" <th>2</th>\n",
|
156 |
+
" <td>NousResearch_Nous-Hermes-2-Mixtral-8x7B-DPO_main</td>\n",
|
157 |
" <td>2024-03-02</td>\n",
|
158 |
+
" <td>70.43</td>\n",
|
159 |
+
" <td>59.33</td>\n",
|
160 |
+
" <td>64.76</td>\n",
|
161 |
+
" <td>78.53</td>\n",
|
162 |
+
" <td>62.17</td>\n",
|
163 |
+
" <td>71.96</td>\n",
|
164 |
+
" <td>85.42</td>\n",
|
165 |
+
" <td>70.82</td>\n",
|
166 |
" </tr>\n",
|
167 |
" <tr>\n",
|
168 |
" <th>3</th>\n",
|
169 |
+
" <td>mistralai_Mixtral-8x7B-Instruct-v0.1_main</td>\n",
|
170 |
+
" <td>2024-03-02</td>\n",
|
171 |
+
" <td>69.80</td>\n",
|
172 |
+
" <td>55.08</td>\n",
|
173 |
+
" <td>70.79</td>\n",
|
174 |
+
" <td>73.56</td>\n",
|
175 |
+
" <td>59.89</td>\n",
|
176 |
+
" <td>70.60</td>\n",
|
177 |
+
" <td>86.68</td>\n",
|
178 |
+
" <td>72.01</td>\n",
|
179 |
" </tr>\n",
|
180 |
" <tr>\n",
|
181 |
" <th>4</th>\n",
|
182 |
" <td>deepseek-ai_deepseek-llm-67b-chat_main</td>\n",
|
183 |
+
" <td>2024-03-04</td>\n",
|
184 |
+
" <td>67.03</td>\n",
|
185 |
+
" <td>NaN</td>\n",
|
186 |
+
" <td>57.78</td>\n",
|
187 |
+
" <td>79.16</td>\n",
|
188 |
" <td>NaN</td>\n",
|
189 |
" <td>NaN</td>\n",
|
|
|
|
|
|
|
190 |
" <td>NaN</td>\n",
|
191 |
+
" <td>64.16</td>\n",
|
192 |
" </tr>\n",
|
193 |
" <tr>\n",
|
194 |
" <th>...</th>\n",
|
|
|
207 |
" <th>269</th>\n",
|
208 |
" <td>HuggingFaceH4_starcoder2-15b-ift_v18.0</td>\n",
|
209 |
" <td>2024-03-10</td>\n",
|
210 |
+
" <td>11.23</td>\n",
|
211 |
+
" <td>21.63</td>\n",
|
212 |
" <td>NaN</td>\n",
|
213 |
" <td>NaN</td>\n",
|
214 |
+
" <td>0.83</td>\n",
|
215 |
" <td>NaN</td>\n",
|
216 |
" <td>NaN</td>\n",
|
217 |
" <td>NaN</td>\n",
|
|
|
220 |
" <th>270</th>\n",
|
221 |
" <td>HuggingFaceH4_mistral-7b-ift_v49.0</td>\n",
|
222 |
" <td>2024-03-07</td>\n",
|
223 |
+
" <td>10.07</td>\n",
|
224 |
+
" <td>20.15</td>\n",
|
225 |
" <td>NaN</td>\n",
|
226 |
" <td>NaN</td>\n",
|
227 |
+
" <td>0.00</td>\n",
|
228 |
" <td>NaN</td>\n",
|
229 |
" <td>NaN</td>\n",
|
230 |
" <td>NaN</td>\n",
|
|
|
233 |
" <th>271</th>\n",
|
234 |
" <td>HuggingFaceH4_starchat-beta_main</td>\n",
|
235 |
" <td>2024-03-12</td>\n",
|
236 |
+
" <td>8.13</td>\n",
|
237 |
+
" <td>8.13</td>\n",
|
238 |
" <td>NaN</td>\n",
|
239 |
" <td>NaN</td>\n",
|
240 |
" <td>NaN</td>\n",
|
|
|
246 |
" <th>272</th>\n",
|
247 |
" <td>HuggingFaceH4_starcoder2-15b-ift_v7.0</td>\n",
|
248 |
" <td>2024-03-10</td>\n",
|
249 |
+
" <td>7.88</td>\n",
|
250 |
+
" <td>12.57</td>\n",
|
251 |
" <td>NaN</td>\n",
|
252 |
" <td>NaN</td>\n",
|
253 |
+
" <td>3.18</td>\n",
|
254 |
" <td>NaN</td>\n",
|
255 |
" <td>NaN</td>\n",
|
256 |
" <td>NaN</td>\n",
|
|
|
259 |
" <th>273</th>\n",
|
260 |
" <td>HuggingFaceH4_zephyr-7b-beta-ift_v1.1</td>\n",
|
261 |
" <td>2024-03-13</td>\n",
|
262 |
+
" <td>4.71</td>\n",
|
263 |
+
" <td>9.43</td>\n",
|
264 |
" <td>NaN</td>\n",
|
265 |
" <td>NaN</td>\n",
|
266 |
+
" <td>0.00</td>\n",
|
267 |
" <td>NaN</td>\n",
|
268 |
" <td>NaN</td>\n",
|
269 |
" <td>NaN</td>\n",
|
|
|
275 |
],
|
276 |
"text/plain": [
|
277 |
" Model Date Average \\\n",
|
278 |
+
"0 NousResearch_Nous-Hermes-2-Yi-34B_main 2024-03-04 74.01 \n",
|
279 |
+
"1 deepseek-ai_deepseek-llm-67b-chat_main 2024-03-05 71.62 \n",
|
280 |
+
"2 NousResearch_Nous-Hermes-2-Mixtral-8x7B-DPO_main 2024-03-02 70.43 \n",
|
281 |
+
"3 mistralai_Mixtral-8x7B-Instruct-v0.1_main 2024-03-02 69.80 \n",
|
282 |
+
"4 deepseek-ai_deepseek-llm-67b-chat_main 2024-03-04 67.03 \n",
|
283 |
".. ... ... ... \n",
|
284 |
+
"269 HuggingFaceH4_starcoder2-15b-ift_v18.0 2024-03-10 11.23 \n",
|
285 |
+
"270 HuggingFaceH4_mistral-7b-ift_v49.0 2024-03-07 10.07 \n",
|
286 |
+
"271 HuggingFaceH4_starchat-beta_main 2024-03-12 8.13 \n",
|
287 |
+
"272 HuggingFaceH4_starcoder2-15b-ift_v7.0 2024-03-10 7.88 \n",
|
288 |
+
"273 HuggingFaceH4_zephyr-7b-beta-ift_v1.1 2024-03-13 4.71 \n",
|
289 |
"\n",
|
290 |
+
" Ifeval Truthfulqa Winogrande Gsm8k Mmlu Hellaswag Arc \n",
|
291 |
+
"0 NaN 61.44 80.58 NaN 76.24 83.79 68.00 \n",
|
292 |
+
"1 55.27 NaN NaN 76.12 71.18 83.94 NaN \n",
|
293 |
+
"2 59.33 64.76 78.53 62.17 71.96 85.42 70.82 \n",
|
294 |
+
"3 55.08 70.79 73.56 59.89 70.60 86.68 72.01 \n",
|
295 |
+
"4 NaN 57.78 79.16 NaN NaN NaN 64.16 \n",
|
296 |
+
".. ... ... ... ... ... ... ... \n",
|
297 |
+
"269 21.63 NaN NaN 0.83 NaN NaN NaN \n",
|
298 |
+
"270 20.15 NaN NaN 0.00 NaN NaN NaN \n",
|
299 |
+
"271 8.13 NaN NaN NaN NaN NaN NaN \n",
|
300 |
+
"272 12.57 NaN NaN 3.18 NaN NaN NaN \n",
|
301 |
+
"273 9.43 NaN NaN 0.00 NaN NaN NaN \n",
|
302 |
"\n",
|
303 |
"[274 rows x 10 columns]"
|
304 |
]
|
305 |
},
|
306 |
+
"execution_count": 5,
|
307 |
"metadata": {},
|
308 |
"output_type": "execute_result"
|
309 |
}
|
|
|
314 |
},
|
315 |
{
|
316 |
"cell_type": "code",
|
317 |
+
"execution_count": 14,
|
318 |
"metadata": {},
|
319 |
"outputs": [
|
320 |
{
|
|
|
339 |
" <tr style=\"text-align: right;\">\n",
|
340 |
" <th></th>\n",
|
341 |
" <th>Model</th>\n",
|
|
|
342 |
" <th>Ifeval</th>\n",
|
343 |
" <th>Truthfulqa</th>\n",
|
344 |
" <th>Winogrande</th>\n",
|
|
|
350 |
" </thead>\n",
|
351 |
" <tbody>\n",
|
352 |
" <tr>\n",
|
353 |
+
" <th>0</th>\n",
|
354 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v41.0</td>\n",
|
355 |
+
" <td>44.36</td>\n",
|
356 |
+
" <td>49.35</td>\n",
|
357 |
+
" <td>72.93</td>\n",
|
358 |
+
" <td>37.30</td>\n",
|
359 |
+
" <td>60.82</td>\n",
|
360 |
+
" <td>79.70</td>\n",
|
361 |
+
" <td>58.36</td>\n",
|
362 |
+
" </tr>\n",
|
363 |
+
" <tr>\n",
|
364 |
+
" <th>1</th>\n",
|
365 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v41.1</td>\n",
|
366 |
+
" <td>47.32</td>\n",
|
367 |
+
" <td>47.89</td>\n",
|
368 |
+
" <td>72.69</td>\n",
|
369 |
+
" <td>36.32</td>\n",
|
370 |
+
" <td>60.34</td>\n",
|
371 |
+
" <td>79.57</td>\n",
|
372 |
+
" <td>57.51</td>\n",
|
373 |
+
" </tr>\n",
|
374 |
+
" <tr>\n",
|
375 |
+
" <th>2</th>\n",
|
376 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v41.10</td>\n",
|
377 |
+
" <td>32.72</td>\n",
|
378 |
+
" <td>51.05</td>\n",
|
379 |
+
" <td>72.45</td>\n",
|
380 |
+
" <td>25.93</td>\n",
|
381 |
+
" <td>59.75</td>\n",
|
382 |
+
" <td>81.92</td>\n",
|
383 |
+
" <td>59.22</td>\n",
|
384 |
+
" </tr>\n",
|
385 |
+
" <tr>\n",
|
386 |
+
" <th>3</th>\n",
|
387 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v41.11</td>\n",
|
388 |
+
" <td>37.89</td>\n",
|
389 |
+
" <td>51.05</td>\n",
|
390 |
+
" <td>64.56</td>\n",
|
391 |
+
" <td>17.59</td>\n",
|
392 |
+
" <td>57.60</td>\n",
|
393 |
+
" <td>77.65</td>\n",
|
394 |
+
" <td>55.89</td>\n",
|
395 |
+
" </tr>\n",
|
396 |
+
" <tr>\n",
|
397 |
+
" <th>4</th>\n",
|
398 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v41.12</td>\n",
|
399 |
+
" <td>37.89</td>\n",
|
400 |
+
" <td>45.94</td>\n",
|
401 |
+
" <td>63.30</td>\n",
|
402 |
+
" <td>21.15</td>\n",
|
403 |
+
" <td>58.50</td>\n",
|
404 |
+
" <td>74.94</td>\n",
|
405 |
+
" <td>52.73</td>\n",
|
406 |
" </tr>\n",
|
407 |
" <tr>\n",
|
408 |
+
" <th>...</th>\n",
|
409 |
+
" <td>...</td>\n",
|
410 |
+
" <td>...</td>\n",
|
411 |
+
" <td>...</td>\n",
|
412 |
+
" <td>...</td>\n",
|
413 |
+
" <td>...</td>\n",
|
414 |
+
" <td>...</td>\n",
|
415 |
+
" <td>...</td>\n",
|
416 |
+
" <td>...</td>\n",
|
417 |
+
" </tr>\n",
|
418 |
+
" <tr>\n",
|
419 |
+
" <th>258</th>\n",
|
420 |
+
" <td>mistralai_Mistral-7B-Instruct-v0.2_main</td>\n",
|
421 |
+
" <td>53.97</td>\n",
|
422 |
+
" <td>70.68</td>\n",
|
423 |
+
" <td>68.82</td>\n",
|
424 |
+
" <td>38.13</td>\n",
|
425 |
+
" <td>59.43</td>\n",
|
426 |
+
" <td>83.45</td>\n",
|
427 |
+
" <td>65.70</td>\n",
|
428 |
+
" </tr>\n",
|
429 |
+
" <tr>\n",
|
430 |
+
" <th>259</th>\n",
|
431 |
+
" <td>mistralai_Mixtral-8x7B-Instruct-v0.1_main</td>\n",
|
432 |
+
" <td>55.08</td>\n",
|
433 |
+
" <td>70.79</td>\n",
|
434 |
+
" <td>73.56</td>\n",
|
435 |
+
" <td>59.89</td>\n",
|
436 |
+
" <td>70.60</td>\n",
|
437 |
+
" <td>86.68</td>\n",
|
438 |
+
" <td>72.01</td>\n",
|
439 |
+
" </tr>\n",
|
440 |
+
" <tr>\n",
|
441 |
+
" <th>260</th>\n",
|
442 |
+
" <td>openchat_openchat-3.5-0106_main</td>\n",
|
443 |
+
" <td>54.71</td>\n",
|
444 |
+
" <td>57.55</td>\n",
|
445 |
+
" <td>72.53</td>\n",
|
446 |
+
" <td>66.19</td>\n",
|
447 |
+
" <td>63.72</td>\n",
|
448 |
+
" <td>80.10</td>\n",
|
449 |
+
" <td>61.01</td>\n",
|
450 |
+
" </tr>\n",
|
451 |
+
" <tr>\n",
|
452 |
+
" <th>261</th>\n",
|
453 |
+
" <td>stabilityai_stablelm-zephyr-3b_main</td>\n",
|
454 |
+
" <td>34.75</td>\n",
|
455 |
+
" <td>46.19</td>\n",
|
456 |
+
" <td>58.41</td>\n",
|
457 |
+
" <td>40.18</td>\n",
|
458 |
+
" <td>45.18</td>\n",
|
459 |
+
" <td>71.57</td>\n",
|
460 |
+
" <td>45.82</td>\n",
|
461 |
+
" </tr>\n",
|
462 |
+
" <tr>\n",
|
463 |
+
" <th>262</th>\n",
|
464 |
+
" <td>teknium_OpenHermes-2.5-Mistral-7B_main</td>\n",
|
465 |
+
" <td>52.68</td>\n",
|
466 |
+
" <td>58.62</td>\n",
|
467 |
+
" <td>72.14</td>\n",
|
468 |
+
" <td>54.06</td>\n",
|
469 |
+
" <td>63.01</td>\n",
|
470 |
+
" <td>82.34</td>\n",
|
471 |
+
" <td>62.97</td>\n",
|
472 |
+
" </tr>\n",
|
473 |
+
" </tbody>\n",
|
474 |
+
"</table>\n",
|
475 |
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"<p>263 rows × 8 columns</p>\n",
|
476 |
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|
477 |
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],
|
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|
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" Model Ifeval Truthfulqa \\\n",
|
480 |
+
"0 HuggingFaceH4_mistral-7b-ift_v41.0 44.36 49.35 \n",
|
481 |
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"1 HuggingFaceH4_mistral-7b-ift_v41.1 47.32 47.89 \n",
|
482 |
+
"2 HuggingFaceH4_mistral-7b-ift_v41.10 32.72 51.05 \n",
|
483 |
+
"3 HuggingFaceH4_mistral-7b-ift_v41.11 37.89 51.05 \n",
|
484 |
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"4 HuggingFaceH4_mistral-7b-ift_v41.12 37.89 45.94 \n",
|
485 |
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".. ... ... ... \n",
|
486 |
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"258 mistralai_Mistral-7B-Instruct-v0.2_main 53.97 70.68 \n",
|
487 |
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"259 mistralai_Mixtral-8x7B-Instruct-v0.1_main 55.08 70.79 \n",
|
488 |
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"260 openchat_openchat-3.5-0106_main 54.71 57.55 \n",
|
489 |
+
"261 stabilityai_stablelm-zephyr-3b_main 34.75 46.19 \n",
|
490 |
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"262 teknium_OpenHermes-2.5-Mistral-7B_main 52.68 58.62 \n",
|
491 |
+
"\n",
|
492 |
+
" Winogrande Gsm8k Mmlu Hellaswag Arc \n",
|
493 |
+
"0 72.93 37.30 60.82 79.70 58.36 \n",
|
494 |
+
"1 72.69 36.32 60.34 79.57 57.51 \n",
|
495 |
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"2 72.45 25.93 59.75 81.92 59.22 \n",
|
496 |
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"3 64.56 17.59 57.60 77.65 55.89 \n",
|
497 |
+
"4 63.30 21.15 58.50 74.94 52.73 \n",
|
498 |
+
".. ... ... ... ... ... \n",
|
499 |
+
"258 68.82 38.13 59.43 83.45 65.70 \n",
|
500 |
+
"259 73.56 59.89 70.60 86.68 72.01 \n",
|
501 |
+
"260 72.53 66.19 63.72 80.10 61.01 \n",
|
502 |
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"261 58.41 40.18 45.18 71.57 45.82 \n",
|
503 |
+
"262 72.14 54.06 63.01 82.34 62.97 \n",
|
504 |
+
"\n",
|
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"[263 rows x 8 columns]"
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
543 |
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" <th></th>\n",
|
544 |
+
" <th>Model</th>\n",
|
545 |
+
" <th>Date</th>\n",
|
546 |
+
" <th>Ifeval</th>\n",
|
547 |
+
" <th>Truthfulqa</th>\n",
|
548 |
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" <th>Winogrande</th>\n",
|
549 |
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|
550 |
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|
551 |
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|
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|
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|
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|
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|
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" <tr>\n",
|
557 |
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" <th>0</th>\n",
|
558 |
+
" <td>NousResearch_Nous-Hermes-2-Yi-34B_main</td>\n",
|
559 |
+
" <td>2024-03-04</td>\n",
|
560 |
+
" <td>39.00</td>\n",
|
561 |
+
" <td>61.44</td>\n",
|
562 |
+
" <td>80.58</td>\n",
|
563 |
+
" <td>67.93</td>\n",
|
564 |
+
" <td>76.24</td>\n",
|
565 |
+
" <td>83.79</td>\n",
|
566 |
+
" <td>68.00</td>\n",
|
567 |
+
" </tr>\n",
|
568 |
+
" <tr>\n",
|
569 |
+
" <th>1</th>\n",
|
570 |
+
" <td>deepseek-ai_deepseek-llm-67b-chat_main</td>\n",
|
571 |
+
" <td>2024-03-05</td>\n",
|
572 |
+
" <td>55.27</td>\n",
|
573 |
+
" <td>57.78</td>\n",
|
574 |
+
" <td>79.16</td>\n",
|
575 |
+
" <td>76.12</td>\n",
|
576 |
+
" <td>71.18</td>\n",
|
577 |
+
" <td>83.94</td>\n",
|
578 |
+
" <td>64.16</td>\n",
|
579 |
+
" </tr>\n",
|
580 |
+
" <tr>\n",
|
581 |
+
" <th>2</th>\n",
|
582 |
+
" <td>NousResearch_Nous-Hermes-2-Mixtral-8x7B-DPO_main</td>\n",
|
583 |
+
" <td>2024-03-02</td>\n",
|
584 |
+
" <td>59.33</td>\n",
|
585 |
+
" <td>64.76</td>\n",
|
586 |
+
" <td>78.53</td>\n",
|
587 |
+
" <td>62.17</td>\n",
|
588 |
+
" <td>71.96</td>\n",
|
589 |
+
" <td>85.42</td>\n",
|
590 |
+
" <td>70.82</td>\n",
|
591 |
+
" </tr>\n",
|
592 |
+
" <tr>\n",
|
593 |
+
" <th>3</th>\n",
|
594 |
+
" <td>mistralai_Mixtral-8x7B-Instruct-v0.1_main</td>\n",
|
595 |
+
" <td>2024-03-02</td>\n",
|
596 |
+
" <td>55.08</td>\n",
|
597 |
+
" <td>70.79</td>\n",
|
598 |
+
" <td>73.56</td>\n",
|
599 |
+
" <td>59.89</td>\n",
|
600 |
+
" <td>70.60</td>\n",
|
601 |
+
" <td>86.68</td>\n",
|
602 |
+
" <td>72.01</td>\n",
|
603 |
+
" </tr>\n",
|
604 |
+
" <tr>\n",
|
605 |
+
" <th>4</th>\n",
|
606 |
+
" <td>deepseek-ai_deepseek-llm-67b-chat_main</td>\n",
|
607 |
+
" <td>2024-03-04</td>\n",
|
608 |
+
" <td>55.27</td>\n",
|
609 |
+
" <td>57.78</td>\n",
|
610 |
+
" <td>79.16</td>\n",
|
611 |
+
" <td>76.12</td>\n",
|
612 |
+
" <td>71.18</td>\n",
|
613 |
+
" <td>83.94</td>\n",
|
614 |
+
" <td>64.16</td>\n",
|
615 |
+
" </tr>\n",
|
616 |
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" <tr>\n",
|
617 |
+
" <th>...</th>\n",
|
618 |
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" <td>...</td>\n",
|
619 |
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" <td>...</td>\n",
|
620 |
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" <td>...</td>\n",
|
621 |
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" <td>...</td>\n",
|
622 |
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" <td>...</td>\n",
|
623 |
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" <td>...</td>\n",
|
624 |
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" <td>...</td>\n",
|
625 |
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" <td>...</td>\n",
|
626 |
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" <td>...</td>\n",
|
627 |
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" </tr>\n",
|
628 |
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" <tr>\n",
|
629 |
+
" <th>269</th>\n",
|
630 |
+
" <td>HuggingFaceH4_starcoder2-15b-ift_v18.0</td>\n",
|
631 |
+
" <td>2024-03-10</td>\n",
|
632 |
+
" <td>21.63</td>\n",
|
633 |
+
" <td>NaN</td>\n",
|
634 |
+
" <td>NaN</td>\n",
|
635 |
+
" <td>0.83</td>\n",
|
636 |
+
" <td>NaN</td>\n",
|
637 |
+
" <td>NaN</td>\n",
|
638 |
+
" <td>NaN</td>\n",
|
639 |
+
" </tr>\n",
|
640 |
+
" <tr>\n",
|
641 |
+
" <th>270</th>\n",
|
642 |
+
" <td>HuggingFaceH4_mistral-7b-ift_v49.0</td>\n",
|
643 |
+
" <td>2024-03-07</td>\n",
|
644 |
+
" <td>20.15</td>\n",
|
645 |
+
" <td>NaN</td>\n",
|
646 |
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" <td>NaN</td>\n",
|
647 |
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" <td>0.00</td>\n",
|
648 |
+
" <td>NaN</td>\n",
|
649 |
+
" <td>NaN</td>\n",
|
650 |
+
" <td>NaN</td>\n",
|
651 |
+
" </tr>\n",
|
652 |
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" <tr>\n",
|
653 |
+
" <th>271</th>\n",
|
654 |
+
" <td>HuggingFaceH4_starchat-beta_main</td>\n",
|
655 |
+
" <td>2024-03-12</td>\n",
|
656 |
+
" <td>8.13</td>\n",
|
657 |
+
" <td>NaN</td>\n",
|
658 |
+
" <td>NaN</td>\n",
|
659 |
+
" <td>NaN</td>\n",
|
660 |
+
" <td>NaN</td>\n",
|
661 |
+
" <td>NaN</td>\n",
|
662 |
+
" <td>NaN</td>\n",
|
663 |
+
" </tr>\n",
|
664 |
+
" <tr>\n",
|
665 |
+
" <th>272</th>\n",
|
666 |
+
" <td>HuggingFaceH4_starcoder2-15b-ift_v7.0</td>\n",
|
667 |
+
" <td>2024-03-10</td>\n",
|
668 |
+
" <td>12.57</td>\n",
|
669 |
+
" <td>NaN</td>\n",
|
670 |
+
" <td>NaN</td>\n",
|
671 |
+
" <td>3.18</td>\n",
|
672 |
" <td>NaN</td>\n",
|
673 |
" <td>NaN</td>\n",
|
674 |
" <td>NaN</td>\n",
|
675 |
+
" </tr>\n",
|
676 |
+
" <tr>\n",
|
677 |
+
" <th>273</th>\n",
|
678 |
+
" <td>HuggingFaceH4_zephyr-7b-beta-ift_v1.1</td>\n",
|
679 |
+
" <td>2024-03-13</td>\n",
|
680 |
+
" <td>9.43</td>\n",
|
681 |
" <td>NaN</td>\n",
|
682 |
" <td>NaN</td>\n",
|
683 |
+
" <td>0.00</td>\n",
|
684 |
" <td>NaN</td>\n",
|
685 |
" <td>NaN</td>\n",
|
686 |
" <td>NaN</td>\n",
|
687 |
" </tr>\n",
|
688 |
" </tbody>\n",
|
689 |
"</table>\n",
|
690 |
+
"<p>274 rows × 9 columns</p>\n",
|
691 |
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|
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|
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"text/plain": [
|
694 |
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" Model Date Ifeval \\\n",
|
695 |
+
"0 NousResearch_Nous-Hermes-2-Yi-34B_main 2024-03-04 39.00 \n",
|
696 |
+
"1 deepseek-ai_deepseek-llm-67b-chat_main 2024-03-05 55.27 \n",
|
697 |
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"2 NousResearch_Nous-Hermes-2-Mixtral-8x7B-DPO_main 2024-03-02 59.33 \n",
|
698 |
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"3 mistralai_Mixtral-8x7B-Instruct-v0.1_main 2024-03-02 55.08 \n",
|
699 |
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"4 deepseek-ai_deepseek-llm-67b-chat_main 2024-03-04 55.27 \n",
|
700 |
+
".. ... ... ... \n",
|
701 |
+
"269 HuggingFaceH4_starcoder2-15b-ift_v18.0 2024-03-10 21.63 \n",
|
702 |
+
"270 HuggingFaceH4_mistral-7b-ift_v49.0 2024-03-07 20.15 \n",
|
703 |
+
"271 HuggingFaceH4_starchat-beta_main 2024-03-12 8.13 \n",
|
704 |
+
"272 HuggingFaceH4_starcoder2-15b-ift_v7.0 2024-03-10 12.57 \n",
|
705 |
+
"273 HuggingFaceH4_zephyr-7b-beta-ift_v1.1 2024-03-13 9.43 \n",
|
706 |
+
"\n",
|
707 |
+
" Truthfulqa Winogrande Gsm8k Mmlu Hellaswag Arc \n",
|
708 |
+
"0 61.44 80.58 67.93 76.24 83.79 68.00 \n",
|
709 |
+
"1 57.78 79.16 76.12 71.18 83.94 64.16 \n",
|
710 |
+
"2 64.76 78.53 62.17 71.96 85.42 70.82 \n",
|
711 |
+
"3 70.79 73.56 59.89 70.60 86.68 72.01 \n",
|
712 |
+
"4 57.78 79.16 76.12 71.18 83.94 64.16 \n",
|
713 |
+
".. ... ... ... ... ... ... \n",
|
714 |
+
"269 NaN NaN 0.83 NaN NaN NaN \n",
|
715 |
+
"270 NaN NaN 0.00 NaN NaN NaN \n",
|
716 |
+
"271 NaN NaN NaN NaN NaN NaN \n",
|
717 |
+
"272 NaN NaN 3.18 NaN NaN NaN \n",
|
718 |
+
"273 NaN NaN 0.00 NaN NaN NaN \n",
|
719 |
"\n",
|
720 |
+
"[274 rows x 9 columns]"
|
|
|
|
|
721 |
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|
722 |
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|
723 |
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"execution_count": 16,
|
724 |
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|
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|
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|
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|
728 |
"source": [
|
729 |
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"df[[\"Model\", \"Date\"]].merge(new_df, on=\"Model\", how=\"left\")"
|
730 |
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|
731 |
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|
732 |
{
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