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One of the most common token classification tasks is Named Entity Recognition (NER). NER attempts to find a label for each entity in a sentence, such as a person, location, or organization.</p> <p data-svelte-h="svelte-1aff4p7">This guide will show you how to:</p> <ol data-svelte-h="svelte-oqtrz6"><li>Finetune <a href="https://huggingface.co/distilbert/distilbert-base-uncased" rel="nofollow">DistilBERT</a> on the <a href="https://huggingface.co/datasets/wnut_17" rel="nofollow">WNUT 17</a> dataset to detect new entities.</li> <li>Use your finetuned model for inference.</li></ol> <blockquote class="tip"><p data-svelte-h="svelte-17xuz9c">To see all architectures and checkpoints compatible with this task, we recommend checking the <a href="https://huggingface.co/tasks/token-classification" rel="nofollow">task-page</a>.</p></blockquote> <p data-svelte-h="svelte-1c9nexd">Before you begin, make sure you have all the necessary libraries installed:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->pip install transformers datasets evaluate seqeval<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-k76o1m">We encourage you to login to your Hugging Face account so you can upload and share your model with the community. When prompted, enter your token to login:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> notebook_login

	<span class="hljs-meta">>>> </span>notebook_login()<!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="load-wnut-17-dataset" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#load-wnut-17-dataset"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Load WNUT 17 dataset</span></h2> <p data-svelte-h="svelte-tluco0">Start by loading the WNUT 17 dataset from the 🤗 Datasets library:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

	<span class="hljs-meta">>>> </span>wnut = load_dataset(<span class="hljs-string">"wnut_17"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1m91ua0">Then take a look at an example:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>wnut[<span class="hljs-string">"train"</span>][<span class="hljs-number">0</span>]
	{<span class="hljs-string">'id'</span>: <span class="hljs-string">'0'</span>,
	<span class="hljs-string">'ner_tags'</span>: [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">7</span>, <span class="hljs-number">8</span>, <span class="hljs-number">8</span>, <span class="hljs-number">0</span>, <span class="hljs-number">7</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>],
	<span class="hljs-string">'tokens'</span>: [<span class="hljs-string">'@paulwalk'</span>, <span class="hljs-string">'It'</span>, <span class="hljs-string">"'s"</span>, <span class="hljs-string">'the'</span>, <span class="hljs-string">'view'</span>, <span class="hljs-string">'from'</span>, <span class="hljs-string">'where'</span>, <span class="hljs-string">'I'</span>, <span class="hljs-string">"'m"</span>, <span class="hljs-string">'living'</span>, <span class="hljs-string">'for'</span>, <span class="hljs-string">'two'</span>, <span class="hljs-string">'weeks'</span>, <span class="hljs-string">'.'</span>, <span class="hljs-string">'Empire'</span>, <span class="hljs-string">'State'</span>, <span class="hljs-string">'Building'</span>, <span class="hljs-string">'='</span>, <span class="hljs-string">'ESB'</span>, <span class="hljs-string">'.'</span>, <span class="hljs-string">'Pretty'</span>, <span class="hljs-string">'bad'</span>, <span class="hljs-string">'storm'</span>, <span class="hljs-string">'here'</span>, <span class="hljs-string">'last'</span>, <span class="hljs-string">'evening'</span>, <span class="hljs-string">'.'</span>]
	}<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1684qxr">Each number in <code>ner_tags</code> represents an entity. Convert the numbers to their label names to find out what the entities are:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>label_list = wnut[<span class="hljs-string">"train"</span>].features[<span class="hljs-string">f"ner_tags"</span>].feature.names
	<span class="hljs-meta">>>> </span>label_list
	[
	<span class="hljs-string">"O"</span>,
	<span class="hljs-string">"B-corporation"</span>,
	<span class="hljs-string">"I-corporation"</span>,
	<span class="hljs-string">"B-creative-work"</span>,
	<span class="hljs-string">"I-creative-work"</span>,
	<span class="hljs-string">"B-group"</span>,
	<span class="hljs-string">"I-group"</span>,
	<span class="hljs-string">"B-location"</span>,
	<span class="hljs-string">"I-location"</span>,
	<span class="hljs-string">"B-person"</span>,
	<span class="hljs-string">"I-person"</span>,
	<span class="hljs-string">"B-product"</span>,
	<span class="hljs-string">"I-product"</span>,
	]<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-b2md1a">The letter that prefixes each <code>ner_tag</code> indicates the token position of the entity:</p> <ul data-svelte-h="svelte-13punrg"><li><code>B-</code> indicates the beginning of an entity.</li> <li><code>I-</code> indicates a token is contained inside the same entity (for example, the <code>State</code> token is a part of an entity like
	<code>Empire State Building</code>).</li> <li><code>0</code> indicates the token doesn’t correspond to any entity.</li></ul> <h2 class="relative group"><a id="preprocess" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#preprocess"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Preprocess</span></h2> <iframe class="w-full xl:w-4/6 h-80" src="https://www.youtube-nocookie.com/embed/iY2AZYdZAr0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> <p data-svelte-h="svelte-1pk56gi">The next step is to load a DistilBERT tokenizer to preprocess the <code>tokens</code> field:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer

	<span class="hljs-meta">>>> </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">"distilbert/distilbert-base-uncased"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-el75ld">As you saw in the example <code>tokens</code> field above, it looks like the input has already been tokenized. But the input actually hasn’t been tokenized yet and you’ll need to set <code>is_split_into_words=True</code> to tokenize the words into subwords. For example:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>example = wnut[<span class="hljs-string">"train"</span>][<span class="hljs-number">0</span>]
	<span class="hljs-meta">>>> </span>tokenized_input = tokenizer(example[<span class="hljs-string">"tokens"</span>], is_split_into_words=<span class="hljs-literal">True</span>)
	<span class="hljs-meta">>>> </span>tokens = tokenizer.convert_ids_to_tokens(tokenized_input[<span class="hljs-string">"input_ids"</span>])
	<span class="hljs-meta">>>> </span>tokens
	[<span class="hljs-string">'[CLS]'</span>, <span class="hljs-string">'@'</span>, <span class="hljs-string">'paul'</span>, <span class="hljs-string">'##walk'</span>, <span class="hljs-string">'it'</span>, <span class="hljs-string">"'"</span>, <span class="hljs-string">'s'</span>, <span class="hljs-string">'the'</span>, <span class="hljs-string">'view'</span>, <span class="hljs-string">'from'</span>, <span class="hljs-string">'where'</span>, <span class="hljs-string">'i'</span>, <span class="hljs-string">"'"</span>, <span class="hljs-string">'m'</span>, <span class="hljs-string">'living'</span>, <span class="hljs-string">'for'</span>, <span class="hljs-string">'two'</span>, <span class="hljs-string">'weeks'</span>, <span class="hljs-string">'.'</span>, <span class="hljs-string">'empire'</span>, <span class="hljs-string">'state'</span>, <span class="hljs-string">'building'</span>, <span class="hljs-string">'='</span>, <span class="hljs-string">'es'</span>, <span class="hljs-string">'##b'</span>, <span class="hljs-string">'.'</span>, <span class="hljs-string">'pretty'</span>, <span class="hljs-string">'bad'</span>, <span class="hljs-string">'storm'</span>, <span class="hljs-string">'here'</span>, <span class="hljs-string">'last'</span>, <span class="hljs-string">'evening'</span>, <span class="hljs-string">'.'</span>, <span class="hljs-string">'[SEP]'</span>]<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1lf9iv0">However, this adds some special tokens <code>[CLS]</code> and <code>[SEP]</code> and the subword tokenization creates a mismatch between the input and labels. A single word corresponding to a single label may now be split into two subwords. You’ll need to realign the tokens and labels by:</p> <ol data-svelte-h="svelte-1heekds"><li>Mapping all tokens to their corresponding word with the <a href="https://huggingface.co/docs/transformers/main_classes/tokenizer#transformers.BatchEncoding.word_ids" rel="nofollow"><code>word_ids</code></a> method.</li> <li>Assigning the label <code>-100</code> to the special tokens <code>[CLS]</code> and <code>[SEP]</code> so they’re ignored by the PyTorch loss function (see <a href="https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html" rel="nofollow">CrossEntropyLoss</a>).</li> <li>Only labeling the first token of a given word. Assign <code>-100</code> to other subtokens from the same word.</li></ol> <p data-svelte-h="svelte-yddais">Here is how you can create a function to realign the tokens and labels, and truncate sequences to be no longer than DistilBERT’s maximum input length:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">tokenize_and_align_labels</span>(<span class="hljs-params">examples</span>):
	<span class="hljs-meta">... </span> tokenized_inputs = tokenizer(examples[<span class="hljs-string">"tokens"</span>], truncation=<span class="hljs-literal">True</span>, is_split_into_words=<span class="hljs-literal">True</span>)

	<span class="hljs-meta">... </span> labels = []
	<span class="hljs-meta">... </span> <span class="hljs-keyword">for</span> i, label <span class="hljs-keyword">in</span> <span class="hljs-built_in">enumerate</span>(examples[<span class="hljs-string">f"ner_tags"</span>]):
	<span class="hljs-meta">... </span> word_ids = tokenized_inputs.word_ids(batch_index=i) <span class="hljs-comment"># Map tokens to their respective word.</span>
	<span class="hljs-meta">... </span> previous_word_idx = <span class="hljs-literal">None</span>
	<span class="hljs-meta">... </span> label_ids = []
	<span class="hljs-meta">... </span> <span class="hljs-keyword">for</span> word_idx <span class="hljs-keyword">in</span> word_ids: <span class="hljs-comment"># Set the special tokens to -100.</span>
	<span class="hljs-meta">... </span> <span class="hljs-keyword">if</span> word_idx <span class="hljs-keyword">is</span> <span class="hljs-literal">None</span>:
	<span class="hljs-meta">... </span> label_ids.append(-<span class="hljs-number">100</span>)
	<span class="hljs-meta">... </span> <span class="hljs-keyword">elif</span> word_idx != previous_word_idx: <span class="hljs-comment"># Only label the first token of a given word.</span>
	<span class="hljs-meta">... </span> label_ids.append(label[word_idx])
	<span class="hljs-meta">... </span> <span class="hljs-keyword">else</span>:
	<span class="hljs-meta">... </span> label_ids.append(-<span class="hljs-number">100</span>)
	<span class="hljs-meta">... </span> previous_word_idx = word_idx
	<span class="hljs-meta">... </span> labels.append(label_ids)

	<span class="hljs-meta">... </span> tokenized_inputs[<span class="hljs-string">"labels"</span>] = labels
	<span class="hljs-meta">... </span> <span class="hljs-keyword">return</span> tokenized_inputs<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1fasmjz">To apply the preprocessing function over the entire dataset, use 🤗 Datasets <a href="https://huggingface.co/docs/datasets/main/en/package_reference/main_classes#datasets.Dataset.map" rel="nofollow">map</a> function. You can speed up the <code>map</code> function by setting <code>batched=True</code> to process multiple elements of the dataset at once:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>tokenized_wnut = wnut.<span class="hljs-built_in">map</span>(tokenize_and_align_labels, batched=<span class="hljs-literal">True</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1jtrvhw">Now create a batch of examples using <a href="/docs/transformers/pr_33892/en/main_classes/data_collator#transformers.DataCollatorWithPadding">DataCollatorWithPadding</a>. It’s more efficient to <em>dynamically pad</em> the sentences to the longest length in a batch during collation, instead of padding the whole dataset to the maximum length.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> DataCollatorForTokenClassification

	<span class="hljs-meta">>>> </span>data_collator = DataCollatorForTokenClassification(tokenizer=tokenizer)<!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="evaluate" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#evaluate"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Evaluate</span></h2> <p data-svelte-h="svelte-434hvn">Including a metric during training is often helpful for evaluating your model’s performance. You can quickly load a evaluation method with the 🤗 <a href="https://huggingface.co/docs/evaluate/index" rel="nofollow">Evaluate</a> library. For this task, load the <a href="https://huggingface.co/spaces/evaluate-metric/seqeval" rel="nofollow">seqeval</a> framework (see the 🤗 Evaluate <a href="https://huggingface.co/docs/evaluate/a_quick_tour" rel="nofollow">quick tour</a> to learn more about how to load and compute a metric). Seqeval actually produces several scores: precision, recall, F1, and accuracy.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">import</span> evaluate

	<span class="hljs-meta">>>> </span>seqeval = evaluate.load(<span class="hljs-string">"seqeval"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-np7vj3">Get the NER labels first, and then create a function that passes your true predictions and true labels to <a href="https://huggingface.co/docs/evaluate/main/en/package_reference/main_classes#evaluate.EvaluationModule.compute" rel="nofollow">compute</a> to calculate the scores:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np

	<span class="hljs-meta">>>> </span>labels = [label_list[i] <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> example[<span class="hljs-string">f"ner_tags"</span>]]


	<span class="hljs-meta">>>> </span><span class="hljs-keyword">def</span> <span class="hljs-title function_">compute_metrics</span>(<span class="hljs-params">p</span>):
	<span class="hljs-meta">... </span> predictions, labels = p
	<span class="hljs-meta">... </span> predictions = np.argmax(predictions, axis=<span class="hljs-number">2</span>)

	<span class="hljs-meta">... </span> true_predictions = [
	<span class="hljs-meta">... </span> [label_list[p] <span class="hljs-keyword">for</span> (p, l) <span class="hljs-keyword">in</span> <span class="hljs-built_in">zip</span>(prediction, label) <span class="hljs-keyword">if</span> l != -<span class="hljs-number">100</span>]
	<span class="hljs-meta">... </span> <span class="hljs-keyword">for</span> prediction, label <span class="hljs-keyword">in</span> <span class="hljs-built_in">zip</span>(predictions, labels)
	<span class="hljs-meta">... </span> ]
	<span class="hljs-meta">... </span> true_labels = [
	<span class="hljs-meta">... </span> [label_list[l] <span class="hljs-keyword">for</span> (p, l) <span class="hljs-keyword">in</span> <span class="hljs-built_in">zip</span>(prediction, label) <span class="hljs-keyword">if</span> l != -<span class="hljs-number">100</span>]
	<span class="hljs-meta">... </span> <span class="hljs-keyword">for</span> prediction, label <span class="hljs-keyword">in</span> <span class="hljs-built_in">zip</span>(predictions, labels)
	<span class="hljs-meta">... </span> ]

	<span class="hljs-meta">... </span> results = seqeval.compute(predictions=true_predictions, references=true_labels)
	<span class="hljs-meta">... </span> <span class="hljs-keyword">return</span> {
	<span class="hljs-meta">... </span> <span class="hljs-string">"precision"</span>: results[<span class="hljs-string">"overall_precision"</span>],
	<span class="hljs-meta">... </span> <span class="hljs-string">"recall"</span>: results[<span class="hljs-string">"overall_recall"</span>],
	<span class="hljs-meta">... </span> <span class="hljs-string">"f1"</span>: results[<span class="hljs-string">"overall_f1"</span>],
	<span class="hljs-meta">... </span> <span class="hljs-string">"accuracy"</span>: results[<span class="hljs-string">"overall_accuracy"</span>],
	<span class="hljs-meta">... </span> }<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-183aynn">Your <code>compute_metrics</code> function is ready to go now, and you’ll return to it when you setup your training.</p> <h2 class="relative group"><a id="train" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#train"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Train</span></h2> <p data-svelte-h="svelte-18c6io4">Before you start training your model, create a map of the expected ids to their labels with <code>id2label</code> and <code>label2id</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>id2label = {
	<span class="hljs-meta">... </span> <span class="hljs-number">0</span>: <span class="hljs-string">"O"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">1</span>: <span class="hljs-string">"B-corporation"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">2</span>: <span class="hljs-string">"I-corporation"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">3</span>: <span class="hljs-string">"B-creative-work"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">4</span>: <span class="hljs-string">"I-creative-work"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">5</span>: <span class="hljs-string">"B-group"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">6</span>: <span class="hljs-string">"I-group"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">7</span>: <span class="hljs-string">"B-location"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">8</span>: <span class="hljs-string">"I-location"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">9</span>: <span class="hljs-string">"B-person"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">10</span>: <span class="hljs-string">"I-person"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">11</span>: <span class="hljs-string">"B-product"</span>,
	<span class="hljs-meta">... </span> <span class="hljs-number">12</span>: <span class="hljs-string">"I-product"</span>,
	<span class="hljs-meta">... </span>}
	<span class="hljs-meta">>>> </span>label2id = {
	<span class="hljs-meta">... </span> <span class="hljs-string">"O"</span>: <span class="hljs-number">0</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-corporation"</span>: <span class="hljs-number">1</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-corporation"</span>: <span class="hljs-number">2</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-creative-work"</span>: <span class="hljs-number">3</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-creative-work"</span>: <span class="hljs-number">4</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-group"</span>: <span class="hljs-number">5</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-group"</span>: <span class="hljs-number">6</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-location"</span>: <span class="hljs-number">7</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-location"</span>: <span class="hljs-number">8</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-person"</span>: <span class="hljs-number">9</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-person"</span>: <span class="hljs-number">10</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"B-product"</span>: <span class="hljs-number">11</span>,
	<span class="hljs-meta">... </span> <span class="hljs-string">"I-product"</span>: <span class="hljs-number">12</span>,
	<span class="hljs-meta">... </span>}<!-- HTML_TAG_END --></pre></div> <blockquote class="tip"><p data-svelte-h="svelte-us7743">If you aren’t familiar with finetuning a model with the <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.Trainer">Trainer</a>, take a look at the basic tutorial <a href="../training#train-with-pytorch-trainer">here</a>!</p></blockquote> <p data-svelte-h="svelte-dcof9v">You’re ready to start training your model now! Load DistilBERT with <a href="/docs/transformers/pr_33892/en/model_doc/auto#transformers.AutoModelForTokenClassification">AutoModelForTokenClassification</a> along with the number of expected labels, and the label mappings:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModelForTokenClassification, TrainingArguments, Trainer

	<span class="hljs-meta">>>> </span>model = AutoModelForTokenClassification.from_pretrained(
	<span class="hljs-meta">... </span> <span class="hljs-string">"distilbert/distilbert-base-uncased"</span>, num_labels=<span class="hljs-number">13</span>, id2label=id2label, label2id=label2id
	<span class="hljs-meta">... </span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-l42k0i">At this point, only three steps remain:</p> <ol data-svelte-h="svelte-1n0ltpu"><li>Define your training hyperparameters in <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.TrainingArguments">TrainingArguments</a>. The only required parameter is <code>output_dir</code> which specifies where to save your model. You’ll push this model to the Hub by setting <code>push_to_hub=True</code> (you need to be signed in to Hugging Face to upload your model). At the end of each epoch, the <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.Trainer">Trainer</a> will evaluate the seqeval scores and save the training checkpoint.</li> <li>Pass the training arguments to <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.Trainer">Trainer</a> along with the model, dataset, tokenizer, data collator, and <code>compute_metrics</code> function.</li> <li>Call <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.Trainer.train">train()</a> to finetune your model.</li></ol> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>training_args = TrainingArguments(
	<span class="hljs-meta">... </span> output_dir=<span class="hljs-string">"my_awesome_wnut_model"</span>,
	<span class="hljs-meta">... </span> learning_rate=<span class="hljs-number">2e-5</span>,
	<span class="hljs-meta">... </span> per_device_train_batch_size=<span class="hljs-number">16</span>,
	<span class="hljs-meta">... </span> per_device_eval_batch_size=<span class="hljs-number">16</span>,
	<span class="hljs-meta">... </span> num_train_epochs=<span class="hljs-number">2</span>,
	<span class="hljs-meta">... </span> weight_decay=<span class="hljs-number">0.01</span>,
	<span class="hljs-meta">... </span> eval_strategy=<span class="hljs-string">"epoch"</span>,
	<span class="hljs-meta">... </span> save_strategy=<span class="hljs-string">"epoch"</span>,
	<span class="hljs-meta">... </span> load_best_model_at_end=<span class="hljs-literal">True</span>,
	<span class="hljs-meta">... </span> push_to_hub=<span class="hljs-literal">True</span>,
	<span class="hljs-meta">... </span>)

	<span class="hljs-meta">>>> </span>trainer = Trainer(
	<span class="hljs-meta">... </span> model=model,
	<span class="hljs-meta">... </span> args=training_args,
	<span class="hljs-meta">... </span> train_dataset=tokenized_wnut[<span class="hljs-string">"train"</span>],
	<span class="hljs-meta">... </span> eval_dataset=tokenized_wnut[<span class="hljs-string">"test"</span>],
	<span class="hljs-meta">... </span> processing_class=tokenizer,
	<span class="hljs-meta">... </span> data_collator=data_collator,
	<span class="hljs-meta">... </span> compute_metrics=compute_metrics,
	<span class="hljs-meta">... </span>)

	<span class="hljs-meta">>>> </span>trainer.train()<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1cccdht">Once training is completed, share your model to the Hub with the <a href="/docs/transformers/pr_33892/en/main_classes/trainer#transformers.Trainer.push_to_hub">push_to_hub()</a> method so everyone can use your model:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>trainer.push_to_hub()<!-- HTML_TAG_END --></pre></div> <blockquote class="tip"><p data-svelte-h="svelte-1iz8pdp">For a more in-depth example of how to finetune a model for token classification, take a look at the corresponding
	<a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/token_classification.ipynb" rel="nofollow">PyTorch notebook</a>.</p></blockquote> <h2 class="relative group"><a id="inference" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#inference"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Inference</span></h2> <p data-svelte-h="svelte-633ppb">Great, now that you’ve finetuned a model, you can use it for inference!</p> <p data-svelte-h="svelte-o1jbfg">Grab some text you’d like to run inference on:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>text = <span class="hljs-string">"The Golden State Warriors are an American professional basketball team based in San Francisco."</span><!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-19fizfm">The simplest way to try out your finetuned model for inference is to use it in a <a href="/docs/transformers/pr_33892/en/main_classes/pipelines#transformers.pipeline">pipeline()</a>. Instantiate a <code>pipeline</code> for NER with your model, and pass your text to it:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> pipeline

	<span class="hljs-meta">>>> </span>classifier = pipeline(<span class="hljs-string">"ner"</span>, model=<span class="hljs-string">"stevhliu/my_awesome_wnut_model"</span>)
	<span class="hljs-meta">>>> </span>classifier(text)
	[{<span class="hljs-string">'entity'</span>: <span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'score'</span>: <span class="hljs-number">0.42658573</span>,
	<span class="hljs-string">'index'</span>: <span class="hljs-number">2</span>,
	<span class="hljs-string">'word'</span>: <span class="hljs-string">'golden'</span>,
	<span class="hljs-string">'start'</span>: <span class="hljs-number">4</span>,
	<span class="hljs-string">'end'</span>: <span class="hljs-number">10</span>},
	{<span class="hljs-string">'entity'</span>: <span class="hljs-string">'I-location'</span>,
	<span class="hljs-string">'score'</span>: <span class="hljs-number">0.35856336</span>,
	<span class="hljs-string">'index'</span>: <span class="hljs-number">3</span>,
	<span class="hljs-string">'word'</span>: <span class="hljs-string">'state'</span>,
	<span class="hljs-string">'start'</span>: <span class="hljs-number">11</span>,
	<span class="hljs-string">'end'</span>: <span class="hljs-number">16</span>},
	{<span class="hljs-string">'entity'</span>: <span class="hljs-string">'B-group'</span>,
	<span class="hljs-string">'score'</span>: <span class="hljs-number">0.3064001</span>,
	<span class="hljs-string">'index'</span>: <span class="hljs-number">4</span>,
	<span class="hljs-string">'word'</span>: <span class="hljs-string">'warriors'</span>,
	<span class="hljs-string">'start'</span>: <span class="hljs-number">17</span>,
	<span class="hljs-string">'end'</span>: <span class="hljs-number">25</span>},
	{<span class="hljs-string">'entity'</span>: <span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'score'</span>: <span class="hljs-number">0.65523505</span>,
	<span class="hljs-string">'index'</span>: <span class="hljs-number">13</span>,
	<span class="hljs-string">'word'</span>: <span class="hljs-string">'san'</span>,
	<span class="hljs-string">'start'</span>: <span class="hljs-number">80</span>,
	<span class="hljs-string">'end'</span>: <span class="hljs-number">83</span>},
	{<span class="hljs-string">'entity'</span>: <span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'score'</span>: <span class="hljs-number">0.4668663</span>,
	<span class="hljs-string">'index'</span>: <span class="hljs-number">14</span>,
	<span class="hljs-string">'word'</span>: <span class="hljs-string">'francisco'</span>,
	<span class="hljs-string">'start'</span>: <span class="hljs-number">84</span>,
	<span class="hljs-string">'end'</span>: <span class="hljs-number">93</span>}]<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1njl8vm">You can also manually replicate the results of the <code>pipeline</code> if you’d like:</p> <p data-svelte-h="svelte-1qcz1wr">Tokenize the text and return PyTorch tensors:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer

	<span class="hljs-meta">>>> </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">"stevhliu/my_awesome_wnut_model"</span>)
	<span class="hljs-meta">>>> </span>inputs = tokenizer(text, return_tensors=<span class="hljs-string">"pt"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-f3g043">Pass your inputs to the model and return the <code>logits</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModelForTokenClassification

	<span class="hljs-meta">>>> </span>model = AutoModelForTokenClassification.from_pretrained(<span class="hljs-string">"stevhliu/my_awesome_wnut_model"</span>)
	<span class="hljs-meta">>>> </span><span class="hljs-keyword">with</span> torch.no_grad():
	<span class="hljs-meta">... </span> logits = model(**inputs).logits<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-6mgrol">Get the class with the highest probability, and use the model’s <code>id2label</code> mapping to convert it to a text label:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span>predictions = torch.argmax(logits, dim=<span class="hljs-number">2</span>)
	<span class="hljs-meta">>>> </span>predicted_token_class = [model.config.id2label[t.item()] <span class="hljs-keyword">for</span> t <span class="hljs-keyword">in</span> predictions[<span class="hljs-number">0</span>]]
	<span class="hljs-meta">>>> </span>predicted_token_class
	[<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'I-location'</span>,
	<span class="hljs-string">'B-group'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'B-location'</span>,
	<span class="hljs-string">'O'</span>,
	<span class="hljs-string">'O'</span>]<!-- HTML_TAG_END --></pre></div> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/transformers/blob/main/docs/source/en/tasks/token_classification.md" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg> <span data-svelte-h="svelte-zjs2n5"><span class="underline">Update</span> on GitHub</span></a> <p></p>

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