mirror of https://github.com/inclusionAI/AReaL
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<h1>Evaluation</h1>
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<h2> Contents </h2>
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<nav aria-label="Page">
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<ul class="visible nav section-nav flex-column">
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#setup-evaluation-environment">Setup Evaluation Environment</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#install-dependencies-and-run-evaluation">Install Dependencies and Run Evaluation</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#command-line-parameters">Command Line Parameters</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#evaluation-results">Evaluation Results</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#metrics-explanation">Metrics Explanation</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#configuration-details">Configuration Details</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#sampling-parameters">Sampling Parameters</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#runtime-expectations">Runtime Expectations</a></li>
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<section class="tex2jax_ignore mathjax_ignore" id="evaluation">
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<h1>Evaluation<a class="headerlink" href="#evaluation" title="Link to this heading">#</a></h1>
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<p>The evaluation code is located in the <code class="docutils literal notranslate"><span class="pre">evaluation</span></code> folder of the repository. Following the previous tutorial, trained checkpoints will be saved under <code class="docutils literal notranslate"><span class="pre">/storage/ray/experiments/checkpoints/root/</span></code>.</p>
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<section id="setup-evaluation-environment">
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<h2>Setup Evaluation Environment<a class="headerlink" href="#setup-evaluation-environment" title="Link to this heading">#</a></h2>
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<p>Start a new container to execute the evaluation script. <strong>Note</strong>: Evaluation requires updates to certain Python libraries, so avoid using the training container for this task.</p>
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker<span class="w"> </span>run<span class="w"> </span>-d<span class="w"> </span>--name<span class="w"> </span>areal-eval<span class="w"> </span>--privileged<span class="w"> </span>--gpus<span class="w"> </span>all<span class="w"> </span>--network<span class="w"> </span>host<span class="w"> </span>--shm-size<span class="w"> </span>700g<span class="w"> </span>-v<span class="w"> </span>/storage:/storage<span class="w"> </span>ghcr.io/inclusionai/areal-runtime:v0.3.0<span class="w"> </span>/bin/bash<span class="w"> </span>-c<span class="w"> </span><span class="s2">"tail -f /dev/null"</span>
|
|
docker<span class="w"> </span><span class="nb">exec</span><span class="w"> </span>-it<span class="w"> </span>areal-eval<span class="w"> </span>bash
|
|
</pre></div>
|
|
</div>
|
|
</section>
|
|
<section id="install-dependencies-and-run-evaluation">
|
|
<h2>Install Dependencies and Run Evaluation<a class="headerlink" href="#install-dependencies-and-run-evaluation" title="Link to this heading">#</a></h2>
|
|
<p>Execute the following commands inside the Docker container:</p>
|
|
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">cd</span><span class="w"> </span>/storage/codes/AReaL/evaluation
|
|
<span class="nb">cd</span><span class="w"> </span>latex2sympy
|
|
pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.
|
|
<span class="nb">cd</span><span class="w"> </span>..
|
|
pip<span class="w"> </span>install<span class="w"> </span>-r<span class="w"> </span>requirements.txt<span class="w"> </span>
|
|
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">vllm</span><span class="o">==</span><span class="m">0</span>.8.5<span class="w"> </span>--no-build-isolation
|
|
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">transformers</span><span class="o">==</span><span class="m">4</span>.51.1
|
|
pip<span class="w"> </span>install<span class="w"> </span>prettytable<span class="w"> </span>timeout_decorator
|
|
mkdir<span class="w"> </span>-p<span class="w"> </span>/storage/ray/eval_output/
|
|
nohup<span class="w"> </span>python<span class="w"> </span>eval_and_aggregate.py<span class="w"> </span><span class="se">\</span>
|
|
<span class="w"> </span>--model_path<span class="w"> </span>/storage/ray/experiments/checkpoints/root/my-exp/my-trial/epoch1epochstep20globalstep20/<span class="w"> </span><span class="se">\</span>
|
|
<span class="w"> </span>--output_path<span class="w"> </span>/storage/ray/eval_output/<span class="w"> </span><span class="se">\</span>
|
|
<span class="w"> </span>--data_names<span class="w"> </span><span class="s2">"math_500,aime24,amc23"</span><span class="w"> </span><span class="se">\</span>
|
|
<span class="w"> </span>--max_gen_tokens<span class="w"> </span><span class="m">32768</span><span class="w"> </span><span class="p">&</span>><span class="w"> </span>/storage/ray/eval_output/eval_and_aggregate_parallel.log<span class="w"> </span><span class="p">&</span>
|
|
</pre></div>
|
|
</div>
|
|
<section id="command-line-parameters">
|
|
<h3>Command Line Parameters<a class="headerlink" href="#command-line-parameters" title="Link to this heading">#</a></h3>
|
|
<ul class="simple">
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">--model_path</span></code></strong>: Path to the saved model parameters</p></li>
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">--output_path</span></code></strong>: Path to store generated answers and log files during evaluation</p></li>
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">--data_names</span></code></strong>: Dataset(s) to evaluate. Multiple datasets can be separated by commas. Available options: <code class="docutils literal notranslate"><span class="pre">math_500</span></code>, <code class="docutils literal notranslate"><span class="pre">math</span></code>, <code class="docutils literal notranslate"><span class="pre">gsm8k</span></code>, <code class="docutils literal notranslate"><span class="pre">train_amc_aime</span></code>, <code class="docutils literal notranslate"><span class="pre">aime24</span></code>, <code class="docutils literal notranslate"><span class="pre">amc23</span></code></p></li>
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">--max_gen_tokens</span></code></strong>: Maximum length of generated answers (default: 32768)</p></li>
|
|
</ul>
|
|
</section>
|
|
</section>
|
|
<section id="evaluation-results">
|
|
<h2>Evaluation Results<a class="headerlink" href="#evaluation-results" title="Link to this heading">#</a></h2>
|
|
<p>The evaluation script will output a results table in the terminal:</p>
|
|
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+----------+---------------+---------------+---------------+------------+---------------+--------+---------+</span>
|
|
<span class="o">|</span> <span class="n">dataset</span> <span class="o">|</span> <span class="n">num_questions</span> <span class="o">|</span> <span class="n">greedy_length</span> <span class="o">|</span> <span class="n">sample_length</span> <span class="o">|</span> <span class="n">greedy_acc</span> <span class="o">|</span> <span class="n">sample_pass</span><span class="o">@</span><span class="mi">1</span> <span class="o">|</span> <span class="k">pass</span><span class="o">@</span><span class="mi">8</span> <span class="o">|</span> <span class="k">pass</span><span class="o">@</span><span class="mi">16</span> <span class="o">|</span>
|
|
<span class="o">+----------+---------------+---------------+---------------+------------+---------------+--------+---------+</span>
|
|
<span class="o">|</span> <span class="n">math_500</span> <span class="o">|</span> <span class="mi">500</span> <span class="o">|</span> <span class="mf">6757.4</span> <span class="o">|</span> <span class="mf">4139.5</span> <span class="o">|</span> <span class="mf">84.4</span> <span class="o">|</span> <span class="mf">92.7</span> <span class="o">|</span> <span class="mf">97.3</span> <span class="o">|</span> <span class="mf">97.7</span> <span class="o">|</span>
|
|
<span class="o">|</span> <span class="n">aime24</span> <span class="o">|</span> <span class="mi">30</span> <span class="o">|</span> <span class="mf">19328.0</span> <span class="o">|</span> <span class="mf">13663.5</span> <span class="o">|</span> <span class="mf">50.0</span> <span class="o">|</span> <span class="mf">50.4</span> <span class="o">|</span> <span class="mf">77.3</span> <span class="o">|</span> <span class="mf">80.0</span> <span class="o">|</span>
|
|
<span class="o">|</span> <span class="n">amc23</span> <span class="o">|</span> <span class="mi">40</span> <span class="o">|</span> <span class="mf">8850.0</span> <span class="o">|</span> <span class="mf">6526.2</span> <span class="o">|</span> <span class="mf">80.0</span> <span class="o">|</span> <span class="mf">90.5</span> <span class="o">|</span> <span class="mf">96.8</span> <span class="o">|</span> <span class="mf">98.8</span> <span class="o">|</span>
|
|
<span class="o">+----------+---------------+---------------+---------------+------------+---------------+--------+---------+</span>
|
|
</pre></div>
|
|
</div>
|
|
<section id="metrics-explanation">
|
|
<h3>Metrics Explanation<a class="headerlink" href="#metrics-explanation" title="Link to this heading">#</a></h3>
|
|
<ul class="simple">
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">{greedy|sample}_length</span></code></strong>: Average answer length under greedy or random sampling strategy</p></li>
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">greedy_acc</span></code></strong>: Average accuracy under greedy sampling</p></li>
|
|
<li><p><strong><code class="docutils literal notranslate"><span class="pre">sample_pass@{k}</span></code></strong>: Probability of generating a correct answer within <code class="docutils literal notranslate"><span class="pre">k</span></code> attempts under random sampling</p></li>
|
|
</ul>
|
|
</section>
|
|
</section>
|
|
<section id="configuration-details">
|
|
<h2>Configuration Details<a class="headerlink" href="#configuration-details" title="Link to this heading">#</a></h2>
|
|
<section id="sampling-parameters">
|
|
<h3>Sampling Parameters<a class="headerlink" href="#sampling-parameters" title="Link to this heading">#</a></h3>
|
|
<ul class="simple">
|
|
<li><p>The evaluation script defaults to averaging 32 samples with temperature 0.6</p></li>
|
|
<li><p>We observed that the <code class="docutils literal notranslate"><span class="pre">enforce_eager</span></code> parameter in vLLM significantly impacts evaluation performance</p></li>
|
|
<li><p>When <code class="docutils literal notranslate"><span class="pre">enforce_eager=True</span></code>, we can reproduce the model performance reported in previous work</p></li>
|
|
<li><p>Without this setting, evaluation results may fall below reported performance</p></li>
|
|
<li><p>Therefore, we enforce <code class="docutils literal notranslate"><span class="pre">enforce_eager=True</span></code> during evaluation</p></li>
|
|
</ul>
|
|
</section>
|
|
<section id="runtime-expectations">
|
|
<h3>Runtime Expectations<a class="headerlink" href="#runtime-expectations" title="Link to this heading">#</a></h3>
|
|
<p>Due to the sampling requirements and <code class="docutils literal notranslate"><span class="pre">enforce_eager</span></code> setting, the evaluation process typically takes considerable time.</p>
|
|
<p>Runtime depends on several factors:</p>
|
|
<ul class="simple">
|
|
<li><p>Maximum generation length</p></li>
|
|
<li><p>Number of questions in the dataset</p></li>
|
|
<li><p>Model size</p></li>
|
|
</ul>
|
|
<p><strong>Performance benchmarks</strong> (on 8x H100 GPUs):</p>
|
|
<ul class="simple">
|
|
<li><p><strong>AIME dataset</strong>: ~80 minutes</p></li>
|
|
<li><p><strong>MATH_500 dataset</strong>: ~160 minutes</p></li>
|
|
</ul>
|
|
</section>
|
|
</section>
|
|
</section>
|
|
|
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<i class="fa-solid fa-list"></i> Contents
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#setup-evaluation-environment">Setup Evaluation Environment</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#command-line-parameters">Command Line Parameters</a></li>
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