import{s as _a,n as $a,o as Ba}from"../chunks/scheduler.5f3e6389.js";import{S as Za,i as Ea,e as j,s as n,c as e,h as va,a as h,d as l,b as p,f as qa,g as u,j as r,k as Aa,l as ka,m as t,n as i,t as o,o as M,p as c}from"../chunks/index.373ab25c.js";import{C as Qa,H as T,E as Na}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.f6d2fa18.js";import{C as os}from"../chunks/CodeBlock.f6cc113c.js";function Wa(ua){let J,js,Ms,hs,y,rs,U,Ts,d,ia="Lighteval provides comprehensive logging and result management through the <code>EvaluationTracker</code> class. This system allows you to save results locally and optionally push them to various platforms for collaboration and analysis.",Js,m,ys,w,oa=`Lighteval automatically saves results and evaluation details in the
directory specified with the <code>--output-dir</code> option. The results are saved in
<code>{output_dir}/results/{model_name}/results_{timestamp}.json</code>. <a href="#example-of-a-result-file">Here is an
example of a result file</a>. The output path can be
any <a href="https://filesystem-spec.readthedocs.io/en/latest/index.html" rel="nofollow">fsspec</a>
compliant path (local, S3, Hugging Face Hub, Google Drive, FTP, etc.).`,Us,I,Ma=`To save detailed evaluation information, you can use the <code>--save-details</code>
option. The details are saved in Parquet files at
<code>{output_dir}/details/{model_name}/{timestamp}/details_{task}_{timestamp}.parquet</code>.`,ds,g,ca=`If you want results to be saved in a custom path structure, you can set the <code>results-path-template</code> option.
This allows you to specify a string template for the path. The template must contain the following
variables: <code>output_dir</code>, <code>model_name</code>, <code>org</code>. For example:
<code>{output_dir}/{org}_{model}</code>. The template will be used to create the path for the results file.`,ms,f,ws,C,ja=`You can push results and evaluation details to the Hugging Face Hub. To do
so, you need to set the <code>--push-to-hub</code> option as well as the <code>--results-org</code>
option. The results are saved in a dataset with the name
<code>{results_org}/{model_org}/{model_name}</code>. To push the details, you need to set
the <code>--save-details</code> option.`,Is,b,ha=`The dataset created will be private by default. You can make it public by
setting the <code>--public-run</code> option.`,gs,q,fs,A,ra=`You can push results to TensorBoard by setting <code>--push-to-tensorboard</code>.
This creates a TensorBoard dashboard in a Hugging Face organization specified with the <code>--results-org</code>
option.`,Cs,_,bs,$,Ta=`You can push results to Weights &amp; Biases by setting <code>--wandb</code>. This initializes a W&amp;B
run and logs the results.`,qs,B,Ja="W&B arguments need to be set in your environment variables:",As,Z,_s,E,ya='You can find a complete list of variables in the <a href="https://docs.wandb.ai/guides/track/environment-variables/" rel="nofollow">W&amp;B documentation</a>.',$s,v,Ua=`If Trackio is available in your environment (<code>pip install lighteval[trackio]</code>), it will be used to log and push results to a
Hugging Face dataset. Choose the dataset name and organization with:`,Bs,k,Zs,Q,Es,N,vs,W,ks,G,Qs,z,Ns,R,Ws,X,da="The detail file contains the following columns:",Gs,F,ma="<li><strong><code>__doc__</code></strong>: The document used for evaluation, containing the gold reference, few-shot examples, and other hyperparameters used for the task.</li> <li><strong><code>__model_response__</code></strong>: Contains model generations, log probabilities, and the input that was sent to the model.</li> <li><strong><code>__metric__</code></strong>: The value of the metrics for this sample.</li>",zs,S,Rs,V,wa="The <code>EvaluationTracker</code> class provides several configuration options for customizing how results are saved and pushed:",Xs,H,Fs,Y,Ss,x,Vs,D,Hs,L,Ys,P,Ia="<li><strong><code>output_dir</code></strong>: Local directory to save evaluation results and logs</li> <li><strong><code>results_path_template</code></strong>: Template for results directory structure</li> <li><strong><code>save_details</code></strong>: Whether to save detailed evaluation records (default: True)</li> <li><strong><code>push_to_hub</code></strong>: Whether to push results to Hugging Face Hub (default: False)</li> <li><strong><code>push_to_tensorboard</code></strong>: Whether to push metrics to TensorBoard (default: False)</li> <li><strong><code>hub_results_org</code></strong>: Hugging Face Hub organization to push results to</li> <li><strong><code>tensorboard_metric_prefix</code></strong>: Prefix for TensorBoard metrics (default: “eval”)</li> <li><strong><code>public</code></strong>: Whether to make Hub datasets public (default: False)</li> <li><strong><code>use_wandb</code></strong>: Whether to log to Weights &amp; Biases or Trackio (default: False)</li>",xs,O,Ds,K,ga="The main results file contains several sections:",Ls,ss,Ps,as,fa="<li><strong><code>config_general</code></strong>: Overall evaluation configuration including model information, timing, and system details</li> <li><strong><code>summary_general</code></strong>: General statistics about the evaluation run</li>",Os,ls,Ks,ts,Ca="<li><strong><code>config_tasks</code></strong>: Configuration details for each evaluated task</li> <li><strong><code>summary_tasks</code></strong>: Task-specific statistics and metadata</li> <li><strong><code>versions</code></strong>: Version information for tasks and datasets</li>",sa,ns,aa,ps,ba="<li><strong><code>results</code></strong>: Actual evaluation metrics and scores for each task</li>",la,es,ta,us,na,is,pa,cs,ea;return y=new Qa({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),U=new T({props:{title:"Saving and Reading Results",local:"saving-and-reading-results",headingTag:"h1"}}),m=new T({props:{title:"Saving Results Locally",local:"saving-results-locally",headingTag:"h2"}}),f=new T({props:{title:"Pushing Results to the Hugging Face Hub",local:"pushing-results-to-the-hugging-face-hub",headingTag:"h2"}}),q=new T({props:{title:"Pushing Results to TensorBoard",local:"pushing-results-to-tensorboard",headingTag:"h2"}}),_=new T({props:{title:"Pushing Results to Weights & Biases or Trackio",local:"pushing-results-to-weights--biases-or-trackio",headingTag:"h2"}}),Z=new os({props:{code:"ZXhwb3J0JTIwV0FOREJfUFJPSkVDVCUzRCUyMmxpZ2h0ZXZhbCUyMg==",highlighted:'<span class="hljs-built_in">export</span> WANDB_PROJECT=<span class="hljs-string">&quot;lighteval&quot;</span>',wrap:!1}}),k=new os({props:{code:"ZXhwb3J0JTIwV0FOREJfU1BBQ0VfSUQlM0QlMjJvcmclMkZuYW1lJTIy",highlighted:'<span class="hljs-built_in">export</span> WANDB_SPACE_ID=<span class="hljs-string">&quot;org/name&quot;</span>',wrap:!1}}),Q=new T({props:{title:"How to Load and Investigate Details",local:"how-to-load-and-investigate-details",headingTag:"h2"}}),N=new T({props:{title:"Loading from Local Detail Files",local:"loading-from-local-detail-files",headingTag:"h3"}}),W=new os({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset
<span class="hljs-keyword">import</span> os
<span class="hljs-keyword">import</span> glob

output_dir = <span class="hljs-string">&quot;evals_doc&quot;</span>
model_name = <span class="hljs-string">&quot;HuggingFaceH4/zephyr-7b-beta&quot;</span>
timestamp = <span class="hljs-string">&quot;latest&quot;</span>
task = <span class="hljs-string">&quot;lighteval|gsm8k|0&quot;</span>

<span class="hljs-keyword">if</span> timestamp == <span class="hljs-string">&quot;latest&quot;</span>:
    path = <span class="hljs-string">f&quot;<span class="hljs-subst">{output_dir}</span>/details/<span class="hljs-subst">{model_name}</span>/*/&quot;</span>
    timestamps = glob.glob(path)
    timestamp = <span class="hljs-built_in">sorted</span>(timestamps)[-<span class="hljs-number">1</span>].split(<span class="hljs-string">&quot;/&quot;</span>)[-<span class="hljs-number">2</span>]
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Latest timestamp: <span class="hljs-subst">{timestamp}</span>&quot;</span>)

details_path = <span class="hljs-string">f&quot;<span class="hljs-subst">{output_dir}</span>/details/<span class="hljs-subst">{model_name}</span>/<span class="hljs-subst">{timestamp}</span>/details_<span class="hljs-subst">{task}</span>_<span class="hljs-subst">{timestamp}</span>.parquet&quot;</span>

<span class="hljs-comment"># Load the details</span>
details = load_dataset(<span class="hljs-string">&quot;parquet&quot;</span>, data_files=details_path, split=<span class="hljs-string">&quot;train&quot;</span>)

<span class="hljs-keyword">for</span> detail <span class="hljs-keyword">in</span> details:
    <span class="hljs-built_in">print</span>(detail)`,wrap:!1}}),G=new T({props:{title:"Loading from the Hugging Face Hub",local:"loading-from-the-hugging-face-hub",headingTag:"h3"}}),z=new os({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBcmVzdWx0c19vcmclMjAlM0QlMjAlMjJTYXlsb3JUd2lmdCUyMiUwQW1vZGVsX25hbWUlMjAlM0QlMjAlMjJIdWdnaW5nRmFjZUg0JTJGemVwaHlyLTdiLWJldGElMjIlMEFzYW5pdGl6ZWRfbW9kZWxfbmFtZSUyMCUzRCUyMG1vZGVsX25hbWUucmVwbGFjZSglMjIlMkYlMjIlMkMlMjAlMjJfXyUyMiklMEF0YXNrJTIwJTNEJTIwJTIybGlnaHRldmFsJTdDZ3NtOGslN0MwJTIyJTBBcHVibGljX3J1biUyMCUzRCUyMEZhbHNlJTBBJTBBZGF0YXNldF9wYXRoJTIwJTNEJTIwZiUyMiU3QnJlc3VsdHNfb3JnJTdEJTJGZGV0YWlsc18lN0JzYW5pdGl6ZWRfbW9kZWxfbmFtZSU3RCU3QidfcHJpdmF0ZSclMjBpZiUyMG5vdCUyMHB1YmxpY19ydW4lMjBlbHNlJTIwJyclN0QlMjIlMEFkZXRhaWxzJTIwJTNEJTIwbG9hZF9kYXRhc2V0KGRhdGFzZXRfcGF0aCUyQyUyMHRhc2sucmVwbGFjZSglMjIlN0MlMjIlMkMlMjAlMjJfJTIyKSUyQyUyMHNwbGl0JTNEJTIybGF0ZXN0JTIyKSUwQSUwQWZvciUyMGRldGFpbCUyMGluJTIwZGV0YWlscyUzQSUwQSUyMCUyMCUyMCUyMHByaW50KGRldGFpbCk=",highlighted:`<span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

results_org = <span class="hljs-string">&quot;SaylorTwift&quot;</span>
model_name = <span class="hljs-string">&quot;HuggingFaceH4/zephyr-7b-beta&quot;</span>
sanitized_model_name = model_name.replace(<span class="hljs-string">&quot;/&quot;</span>, <span class="hljs-string">&quot;__&quot;</span>)
task = <span class="hljs-string">&quot;lighteval|gsm8k|0&quot;</span>
public_run = <span class="hljs-literal">False</span>

dataset_path = <span class="hljs-string">f&quot;<span class="hljs-subst">{results_org}</span>/details_<span class="hljs-subst">{sanitized_model_name}</span><span class="hljs-subst">{<span class="hljs-string">&#x27;_private&#x27;</span> <span class="hljs-keyword">if</span> <span class="hljs-keyword">not</span> public_run <span class="hljs-keyword">else</span> <span class="hljs-string">&#x27;&#x27;</span>}</span>&quot;</span>
details = load_dataset(dataset_path, task.replace(<span class="hljs-string">&quot;|&quot;</span>, <span class="hljs-string">&quot;_&quot;</span>), split=<span class="hljs-string">&quot;latest&quot;</span>)

<span class="hljs-keyword">for</span> detail <span class="hljs-keyword">in</span> details:
    <span class="hljs-built_in">print</span>(detail)`,wrap:!1}}),R=new T({props:{title:"Detail File Structure",local:"detail-file-structure",headingTag:"h2"}}),S=new T({props:{title:"EvaluationTracker Configuration",local:"evaluationtracker-configuration",headingTag:"h2"}}),H=new T({props:{title:"Basic Configuration",local:"basic-configuration",headingTag:"h3"}}),Y=new os({props:{code:"ZnJvbSUyMGxpZ2h0ZXZhbC5sb2dnaW5nLmV2YWx1YXRpb25fdHJhY2tlciUyMGltcG9ydCUyMEV2YWx1YXRpb25UcmFja2VyJTBBJTBBdHJhY2tlciUyMCUzRCUyMEV2YWx1YXRpb25UcmFja2VyKCUwQSUyMCUyMCUyMCUyMG91dHB1dF9kaXIlM0QlMjIuJTJGcmVzdWx0cyUyMiUyQyUwQSUyMCUyMCUyMCUyMHNhdmVfZGV0YWlscyUzRFRydWUlMkMlMEElMjAlMjAlMjAlMjBwdXNoX3RvX2h1YiUzRFRydWUlMkMlMEElMjAlMjAlMjAlMjBodWJfcmVzdWx0c19vcmclM0QlMjJ5b3VyX3VzZXJuYW1lJTIyJTJDJTBBJTIwJTIwJTIwJTIwcHVibGljJTNERmFsc2UlMEEp",highlighted:`<span class="hljs-keyword">from</span> lighteval.logging.evaluation_tracker <span class="hljs-keyword">import</span> EvaluationTracker

tracker = EvaluationTracker(
    output_dir=<span class="hljs-string">&quot;./results&quot;</span>,
    save_details=<span class="hljs-literal">True</span>,
    push_to_hub=<span class="hljs-literal">True</span>,
    hub_results_org=<span class="hljs-string">&quot;your_username&quot;</span>,
    public=<span class="hljs-literal">False</span>
)`,wrap:!1}}),x=new T({props:{title:"Advanced Configuration",local:"advanced-configuration",headingTag:"h3"}}),D=new os({props:{code:"dHJhY2tlciUyMCUzRCUyMEV2YWx1YXRpb25UcmFja2VyKCUwQSUyMCUyMCUyMCUyMG91dHB1dF9kaXIlM0QlMjIuJTJGcmVzdWx0cyUyMiUyQyUwQSUyMCUyMCUyMCUyMHJlc3VsdHNfcGF0aF90ZW1wbGF0ZSUzRCUyMiU3Qm91dHB1dF9kaXIlN0QlMkZjdXN0b20lMkYlN0JvcmclN0RfJTdCbW9kZWwlN0QlMjIlMkMlMEElMjAlMjAlMjAlMjBzYXZlX2RldGFpbHMlM0RUcnVlJTJDJTBBJTIwJTIwJTIwJTIwcHVzaF90b19odWIlM0RUcnVlJTJDJTBBJTIwJTIwJTIwJTIwcHVzaF90b190ZW5zb3Jib2FyZCUzRFRydWUlMkMlMEElMjAlMjAlMjAlMjBodWJfcmVzdWx0c19vcmclM0QlMjJteS1vcmclMjIlMkMlMEElMjAlMjAlMjAlMjB0ZW5zb3Jib2FyZF9tZXRyaWNfcHJlZml4JTNEJTIyZXZhbCUyMiUyQyUwQSUyMCUyMCUyMCUyMHB1YmxpYyUzRFRydWUlMkMlMEElMjAlMjAlMjAlMjB1c2Vfd2FuZGIlM0RUcnVlJTBBKQ==",highlighted:`tracker = EvaluationTracker(
    output_dir=<span class="hljs-string">&quot;./results&quot;</span>,
    results_path_template=<span class="hljs-string">&quot;{output_dir}/custom/{org}_{model}&quot;</span>,
    save_details=<span class="hljs-literal">True</span>,
    push_to_hub=<span class="hljs-literal">True</span>,
    push_to_tensorboard=<span class="hljs-literal">True</span>,
    hub_results_org=<span class="hljs-string">&quot;my-org&quot;</span>,
    tensorboard_metric_prefix=<span class="hljs-string">&quot;eval&quot;</span>,
    public=<span class="hljs-literal">True</span>,
    use_wandb=<span class="hljs-literal">True</span>
)`,wrap:!1}}),L=new T({props:{title:"Key Parameters",local:"key-parameters",headingTag:"h3"}}),O=new T({props:{title:"Result File Structure",local:"result-file-structure",headingTag:"h2"}}),ss=new T({props:{title:"General Configuration",local:"general-configuration",headingTag:"h3"}}),ls=new T({props:{title:"Task-Specific Information",local:"task-specific-information",headingTag:"h3"}}),ns=new T({props:{title:"Results",local:"results",headingTag:"h3"}}),es=new T({props:{title:"Example of a Result File",local:"example-of-a-result-file",headingTag:"h2"}}),us=new os({props:{code:" ",highlighted:`<span class="hljs-punctuation">{</span>
  <span class="hljs-attr">&quot;config_general&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
    <span class="hljs-attr">&quot;lighteval_sha&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;203045a8431bc9b77245c9998e05fc54509ea07f&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;num_fewshot_seeds&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">1</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;max_samples&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">1</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;job_id&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;start_time&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">620979.879320166</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;end_time&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">621004.632108041</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;total_evaluation_time_secondes&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;24.752787875011563&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;model_name&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;gpt2&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;model_sha&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;607a30d783dfa663caf39e06633721c8d4cfcd7e&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;model_dtype&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-literal"><span class="hljs-keyword">null</span></span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;model_size&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;476.2 MB&quot;</span>
  <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;results&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
    <span class="hljs-attr">&quot;lighteval|gsm8k|0&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
      <span class="hljs-attr">&quot;em&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;em_stderr&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;maj@8&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;maj@8_stderr&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span>
    <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;all&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
      <span class="hljs-attr">&quot;em&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;em_stderr&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;maj@8&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span><span class="hljs-punctuation">,</span>
      <span class="hljs-attr">&quot;maj@8_stderr&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0.0</span>
    <span class="hljs-punctuation">}</span>
  <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;versions&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
    <span class="hljs-attr">&quot;lighteval|gsm8k|0&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-number">0</span>
  <span class="hljs-punctuation">}</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;config_tasks&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
    <span class="hljs-attr">&quot;lighteval|gsm8k&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">{</span>
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