lighteval/pr_985/en/_app/immutable/nodes/13.d6eebada.js

import{s as ma,o as pa,n as ha}from"../chunks/scheduler.7da89386.js";import{S as fa,i as ua,g as n,s as a,r as d,A as va,h as l,f as r,c as o,j as $,u as m,x as v,k as x,y as t,a as g,v as p,d as h,t as f,w as u}from"../chunks/index.20910acc.js";import{D as L}from"../chunks/Docstring.41dbb714.js";import{C as _a}from"../chunks/CodeBlock.143bd81e.js";import{E as ba}from"../chunks/ExampleCodeBlock.a84c9d11.js";import{H as me,E as $a}from"../chunks/getInferenceSnippets.375cdad5.js";function xa(Fe){let b,q="Example:",E,T,y;return T=new _a({props:{code:"dHJhY2tlciUyMCUzRCUyMEV2YWx1YXRpb25UcmFja2VyKCUwQSUyMCUyMCUyMCUyMG91dHB1dF9kaXIlM0QlMjIuJTJGZXZhbF9yZXN1bHRzJTIyJTJDJTBBJTIwJTIwJTIwJTIwcHVzaF90b19odWIlM0RUcnVlJTJDJTBBJTIwJTIwJTIwJTIwaHViX3Jlc3VsdHNfb3JnJTNEJTIybXktb3JnJTIyJTJDJTBBJTIwJTIwJTIwJTIwc2F2ZV9kZXRhaWxzJTNEVHJ1ZSUwQSklMEElMEElMjMlMjBMb2clMjBldmFsdWF0aW9uJTIwcmVzdWx0cyUwQXRyYWNrZXIubWV0cmljc19sb2dnZXIuYWRkX21ldHJpYyglMjJhY2N1cmFjeSUyMiUyQyUyMDAuODUpJTBBdHJhY2tlci5kZXRhaWxzX2xvZ2dlci5hZGRfZGV0YWlsKHRhc2tfbmFtZSUzRCUyMnFhJTIyJTJDJTIwcHJlZGljdGlvbiUzRCUyMlBhcmlzJTIyKSUwQSUwQSUyMyUyMFNhdmUlMjBhbGwlMjByZXN1bHRzJTBBdHJhY2tlci5zYXZlKCk=",highlighted:`tracker = EvaluationTracker(
    output_dir=<span class="hljs-string">&quot;./eval_results&quot;</span>,
    push_to_hub=<span class="hljs-literal">True</span>,
    hub_results_org=<span class="hljs-string">&quot;my-org&quot;</span>,
    save_details=<span class="hljs-literal">True</span>
)

<span class="hljs-comment"># Log evaluation results</span>
tracker.metrics_logger.add_metric(<span class="hljs-string">&quot;accuracy&quot;</span>, <span class="hljs-number">0.85</span>)
tracker.details_logger.add_detail(task_name=<span class="hljs-string">&quot;qa&quot;</span>, prediction=<span class="hljs-string">&quot;Paris&quot;</span>)

<span class="hljs-comment"># Save all results</span>
tracker.save()`,wrap:!1}}),{c(){b=n("p"),b.textContent=q,E=a(),d(T.$$.fragment)},l(_){b=l(_,"P",{"data-svelte-h":!0}),v(b)!=="svelte-11lpom8"&&(b.textContent=q),E=o(_),m(T.$$.fragment,_)},m(_,w){g(_,b,w),g(_,E,w),p(T,_,w),y=!0},p:ha,i(_){y||(h(T.$$.fragment,_),y=!0)},o(_){f(T.$$.fragment,_),y=!1},d(_){_&&(r(b),r(E)),u(T,_)}}}function ka(Fe){let b,q,E,T,y,_,w,Se,i,R,ct,pe,Nt="Tracks and manages evaluation results, metrics, and logging for model evaluations.",dt,he,qt="The EvaluationTracker coordinates multiple specialized loggers to track different aspects of model evaluation:",mt,fe,Rt="<li>Details Logger (DetailsLogger): Records per-sample evaluation details and predictions</li> <li>Metrics Logger (MetricsLogger): Tracks aggregate evaluation metrics and scores</li> <li>Versions Logger (VersionsLogger): Records task and dataset versions</li> <li>General Config Logger (GeneralConfigLogger): Stores overall evaluation configuration</li> <li>Task Config Logger (TaskConfigLogger): Maintains per-task configuration details</li>",pt,ue,Wt="The tracker can save results locally and optionally push them to:",ht,ve,Zt="<li>Hugging Face Hub as datasets</li> <li>TensorBoard for visualization</li> <li>Trackio or Weights &amp; Biases for experiment tracking</li>",ft,V,ut,J,W,vt,_e,Xt="Aggregates and returns all the logger’s experiment information in a dictionary.",_t,be,At="This function should be used to gather and display said information at the end of an evaluation run.",bt,G,Z,$t,$e,Yt="Pushes the experiment details (all the model predictions for every step) to the hub.",xt,P,X,kt,xe,Qt="Fully updates the details repository metadata card for the currently evaluated model",Ct,U,A,Lt,ke,Ot="Saves the experiment information and results to files, and to the hub if requested.",ze,Y,Ne,k,Q,Tt,Ce,Kt="Tracks general configuration and runtime information for model evaluations.",yt,Le,ea=`This logger captures key configuration parameters, model details, and timing information
to ensure reproducibility and provide insights into the evaluation process.`,wt,B,O,Dt,Te,ta="Logs the information about the arguments passed to the method.",Mt,F,K,Et,ye,aa="Logs the model information.",qe,ee,Re,C,te,Jt,we,oa="Logger for the experiment details.",It,De,ra="Stores and logs experiment information both at the task and at the sample level.",jt,S,ae,Ht,Me,na="Hashes the details for each task and then for all tasks.",Vt,z,oe,Gt,Ee,la="Stores the relevant information for one sample of one task to the total list of samples stored in the DetailsLogger.",We,re,Ze,D,ne,Pt,Je,sa="Logs the actual scores for each metric of each task.",Ut,N,le,Bt,Ie,ia="Aggregate the metrics for each task and then for all tasks.",Xe,se,Ae,M,ie,Ft,je,ga="Logger of the tasks versions.",St,He,ca="Tasks can have a version number/date, which indicates what is the precise metric definition and dataset version used for an evaluation.",Ye,ge,Qe,H,ce,zt,Ve,da="Logs the different parameters of the current <code>LightevalTask</code> of interest.",Oe,de,Ke,Be,et;return y=new me({props:{title:"Logging",local:"logging",headingTag:"h1"}}),w=new me({props:{title:"EvaluationTracker",local:"lighteval.logging.evaluation_tracker.EvaluationTracker",headingTag:"h2"}}),R=new L({props:{name:"class lighteval.logging.evaluation_tracker.EvaluationTracker",anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker",parameters:[{name:"output_dir",val:": str"},{name:"results_path_template",val:": str | None = None"},{name:"save_details",val:": bool = True"},{name:"push_to_hub",val:": bool = False"},{name:"push_to_tensorboard",val:": bool = False"},{name:"hub_results_org",val:": str | None = ''"},{name:"tensorboard_metric_prefix",val:": str = 'eval'"},{name:"public",val:": bool = False"},{name:"nanotron_run_info",val:": GeneralArgs = None"},{name:"use_wandb",val:": bool = False"}],parametersDescription:[{anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.output_dir",description:"<strong>output_dir</strong> (str) &#x2014; Local directory to save evaluation results and logs",name:"output_dir"},{anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.results_path_template",description:`<strong>results_path_template</strong> (str, optional) &#x2014; Template for results directory structure.
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<p>Dictionary containing all experiment information including config, results, versions, and summaries</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p>dict</p>
`}}),Z=new L({props:{name:"push_to_hub",anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.push_to_hub",parameters:[{name:"date_id",val:": str"},{name:"details",val:": dict"},{name:"results_dict",val:": dict"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/evaluation_tracker.py#L384"}}),X=new L({props:{name:"recreate_metadata_card",anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.recreate_metadata_card",parameters:[{name:"repo_id",val:": str"}],parametersDescription:[{anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.recreate_metadata_card.repo_id",description:"<strong>repo_id</strong> (str) &#x2014; Details dataset repository path on the hub (<code>org/dataset</code>)",name:"repo_id"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/evaluation_tracker.py#L451"}}),A=new L({props:{name:"save",anchor:"lighteval.logging.evaluation_tracker.EvaluationTracker.save",parameters:[],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/evaluation_tracker.py#L244"}}),Y=new me({props:{title:"GeneralConfigLogger",local:"lighteval.logging.info_loggers.GeneralConfigLogger",headingTag:"h2"}}),Q=new L({props:{name:"class lighteval.logging.info_loggers.GeneralConfigLogger",anchor:"lighteval.logging.info_loggers.GeneralConfigLogger",parameters:[],parametersDescription:[{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.lighteval_sha",description:`<strong>lighteval_sha</strong> (str) &#x2014; Git commit SHA of lighteval used for evaluation, enabling exact version reproducibility.
Set to &#x201D;?&#x201D; if not in a git repository.`,name:"lighteval_sha"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.num_fewshot_seeds",description:`<strong>num_fewshot_seeds</strong> (int) &#x2014; Number of random seeds used for few-shot example sampling.</p>
<ul>
<li>If &lt;= 1: Single evaluation with seed=0</li>
<li>If &gt; 1: Multiple evaluations with different few-shot samplings (HELM-style)</li>
</ul>`,name:"num_fewshot_seeds"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.max_samples",description:`<strong>max_samples</strong> (int, optional) &#x2014; Maximum number of samples to evaluate per task.
Only used for debugging - truncates each task&#x2019;s dataset.`,name:"max_samples"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.job_id",description:`<strong>job_id</strong> (int, optional) &#x2014; Slurm job ID if running on a cluster.
Used to cross-reference with scheduler logs.`,name:"job_id"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.start_time",description:`<strong>start_time</strong> (float) &#x2014; Unix timestamp when evaluation started.
Automatically set during logger initialization.`,name:"start_time"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.end_time",description:`<strong>end_time</strong> (float) &#x2014; Unix timestamp when evaluation completed.
Set by calling log_end_time().`,name:"end_time"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.total_evaluation_time_secondes",description:`<strong>total_evaluation_time_secondes</strong> (str) &#x2014; Total runtime in seconds.
Calculated as end_time - start_time.`,name:"total_evaluation_time_secondes"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.model_config",description:`<strong>model_config</strong> (ModelConfig) &#x2014; Complete model configuration settings.
Contains model architecture, tokenizer, and generation parameters.`,name:"model_config"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.model_name",description:`<strong>model_name</strong> (str) &#x2014; Name identifier for the evaluated model.
Extracted from model_config.`,name:"model_name"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L48"}}),O=new L({props:{name:"log_args_info",anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_args_info",parameters:[{name:"num_fewshot_seeds",val:": int"},{name:"max_samples",val:": int | None"},{name:"job_id",val:": str"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_args_info.num_fewshot_seeds",description:"<strong>num_fewshot_seeds</strong> (int) &#x2014; number of few-shot seeds.",name:"num_fewshot_seeds"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_args_info.max_samples",description:"<strong>max_samples</strong> (int | None) &#x2014; maximum number of samples, if None, use all the samples available.",name:"max_samples"},{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_args_info.job_id",description:"<strong>job_id</strong> (str) &#x2014; job ID, used to retrieve logs.",name:"job_id"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L106"}}),K=new L({props:{name:"log_model_info",anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_model_info",parameters:[{name:"model_config",val:": ModelConfig"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.GeneralConfigLogger.log_model_info.model_config",description:"<strong>model_config</strong> &#x2014; the model config used to initialize the model.",name:"model_config"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L123"}}),ee=new me({props:{title:"DetailsLogger",local:"lighteval.logging.info_loggers.DetailsLogger",headingTag:"h2"}}),te=new L({props:{name:"class lighteval.logging.info_loggers.DetailsLogger",anchor:"lighteval.logging.info_loggers.DetailsLogger",parameters:[{name:"hashes",val:": dict = <factory>"},{name:"compiled_hashes",val:": dict = <factory>"},{name:"details",val:": dict = <factory>"},{name:"compiled_details",val:": dict = <factory>"},{name:"compiled_details_over_all_tasks",val:": DetailsLogger.CompiledDetailOverAllTasks = <factory>"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.DetailsLogger.hashes",description:"<strong>hashes</strong> (dict[str, list<code>Hash</code>) &#x2014; Maps each task name to the list of all its samples&#x2019; <code>Hash</code>.",name:"hashes"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.compiled_hashes",description:"<strong>compiled_hashes</strong> (dict[str, CompiledHash) &#x2014; Maps each task name to its <code>CompiledHas</code>, an aggregation of all the individual sample hashes.",name:"compiled_hashes"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.details",description:`<strong>details</strong> (dict[str, list<code>Detail</code>]) &#x2014; Maps each task name to the list of its samples&#x2019; details.
Example: winogrande: [sample1_details, sample2_details, &#x2026;]`,name:"details"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.compiled_details",description:"<strong>compiled_details</strong> (dict[str, <code>CompiledDetail</code>]) &#x2014; : Maps each task name to the list of its samples&#x2019; compiled details.",name:"compiled_details"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.compiled_details_over_all_tasks",description:"<strong>compiled_details_over_all_tasks</strong> (CompiledDetailOverAllTasks) &#x2014; Aggregated details over all the tasks.",name:"compiled_details_over_all_tasks"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L138"}}),ae=new L({props:{name:"aggregate",anchor:"lighteval.logging.info_loggers.DetailsLogger.aggregate",parameters:[],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L277"}}),oe=new L({props:{name:"log",anchor:"lighteval.logging.info_loggers.DetailsLogger.log",parameters:[{name:"task_name",val:": str"},{name:"doc",val:": Doc"},{name:"model_response",val:": ModelResponse"},{name:"metrics",val:": dict"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.DetailsLogger.log.task_name",description:"<strong>task_name</strong> (str) &#x2014; Name of the current task of interest.",name:"task_name"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.log.doc",description:"<strong>doc</strong> (Doc) &#x2014; Current sample that we want to store.",name:"doc"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.log.model_response",description:"<strong>model_response</strong> (ModelResponse) &#x2014; Model outputs for the current sample",name:"model_response"},{anchor:"lighteval.logging.info_loggers.DetailsLogger.log.metrics",description:"<strong>metrics</strong> (dict) &#x2014; Model scores for said sample on the current task&#x2019;s metrics.",name:"metrics"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L253"}}),re=new me({props:{title:"MetricsLogger",local:"lighteval.logging.info_loggers.MetricsLogger",headingTag:"h2"}}),ne=new L({props:{name:"class lighteval.logging.info_loggers.MetricsLogger",anchor:"lighteval.logging.info_loggers.MetricsLogger",parameters:[{name:"metrics_values",val:": dict = <factory>"},{name:"metric_aggregated",val:": dict = <factory>"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.MetricsLogger.metrics_value",description:`<strong>metrics_value</strong> (dict[str, dict[str, list[float]]]) &#x2014; Maps each task to its dictionary of metrics to scores for all the example of the task.
Example: {&#x201C;winogrande|winogrande_xl&#x201D;: {&#x201C;accuracy&#x201D;: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5]}&#x200C;}`,name:"metrics_value"},{anchor:"lighteval.logging.info_loggers.MetricsLogger.metric_aggregated",description:`<strong>metric_aggregated</strong> (dict[str, dict[str, float]]) &#x2014; Maps each task to its dictionary of metrics to aggregated scores over all the example of the task.
Example: {&#x201C;winogrande|winogrande_xl&#x201D;: {&#x201C;accuracy&#x201D;: 0.5}&#x200C;}`,name:"metric_aggregated"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L309"}}),le=new L({props:{name:"aggregate",anchor:"lighteval.logging.info_loggers.MetricsLogger.aggregate",parameters:[{name:"task_dict",val:": dict"},{name:"bootstrap_iters",val:": int = 1000"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.MetricsLogger.aggregate.task_dict",description:"<strong>task_dict</strong> (dict[str, LightevalTask]) &#x2014; used to determine what aggregation function to use for each metric",name:"task_dict"},{anchor:"lighteval.logging.info_loggers.MetricsLogger.aggregate.bootstrap_iters",description:"<strong>bootstrap_iters</strong> (int, optional) &#x2014; Number of runs used to run the statistical bootstrap. Defaults to 1000.",name:"bootstrap_iters"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L330"}}),se=new me({props:{title:"VersionsLogger",local:"lighteval.logging.info_loggers.VersionsLogger",headingTag:"h2"}}),ie=new L({props:{name:"class lighteval.logging.info_loggers.VersionsLogger",anchor:"lighteval.logging.info_loggers.VersionsLogger",parameters:[{name:"versions",val:": dict = <factory>"}],parametersDescription:[{anchor:"lighteval.logging.info_loggers.VersionsLogger.version",description:"<strong>version</strong> (dict[str, int]) &#x2014; Maps the task names with the task versions.",name:"version"}],source:"https://github.com/huggingface/lighteval/blob/vr_985/src/lighteval/logging/info_loggers.py#L406"}}),ge=new me({props:{title:"TaskConfigLogger",local:"lighteval.logging.info_loggers.TaskConfigLogger",headingTag:"h2"}}),ce=new L({props:{name:"class 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