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f,z,m,y,w,u,g,x,H,ee,me,Y,T,_e,J,ue,S,Mr,Ye,Lr,Ir,Je,Rr,Br,Xe,Nr,Wr,$e,Hr,Yr,Vt,Se,Jr,Zt,Ee,er,he,Xr,tr,F,Kr,Ke,Qr,Vr,Qe,Zr,ea,Ve,ta,ra,rr,ve,ar,ae,or,X,aa,Ue,oa,sa,Ze,la,ia,sr,ke,lr,oe,na,Fe,ca,pa,ir,O,da,et,fa,ma,tt,_a,ua,rt,$a,Ea,at,ha,va,ot,ka,Ca,nr,Ce,cr,P,ba,st,Ta,wa,lt,Da,ga,it,Oa,Pa,nt,ja,qa,ct,Aa,za,pr,K,ya,pt,xa,Sa,dt,Ua,Fa,dr,be,fr,Ge,Ga,mr,se,A,Ma,ft,La,Ia,mt,Ra,Ba,_t,Na,Wa,ut,Ha,Ya,$t,Ja,Xa,Ka,te,Qa,Et,Va,Za,ht,eo,to,_r,Te,ro,ur,j,ao,vt,oo,so,kt,lo,io,Ct,no,co,bt,po,fo,Tt,mo,_o,$r,we,Er,De,hr,_,wt,uo,$o,Dt,Eo,ho,gt,vo,ko,Ot,Co,bo,Pt,To,wo,jt,Do,go,qt,Oo,Po,At,jo,qo,vr,G,Ao,zt,zo,yo,yt,xo,So,Me,Uo,Fo,kr,ge,Cr,q,Go,xt,Mo,Lo,St,Io,Ro,Oe,Bo,No,Ut,Wo,Ho,Ft,Yo,Jo,br,Pe,Tr,je,wr,M,Xo,qe,Ko,Qo,Gt,Vo,Zo,Mt,es,ts,Dr,le,rs,Lt,as,os,gr,Ae,Or,Q,ss,It,ls,is,Rt,ns,cs,Pr,ze,jr,L,ps,Bt,ds,fs,Nt,ms,_s,Wt,us,$s,qr,ye,Ar,Le,Es,zr,re,Ht,hs,vs,Yt,ks,Cs,yr,V,bs,Jt,Ts,ws,Ie,Ds,gs,xr,ie,Sr;return m=new Ql({props:{fw:fe[0]}}),x=new Xl({}),T=new Kl({props:{chapter:3,classNames:"absolute z-10 right-0 top-0",notebooks:[{label:"Google Colab",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/hi/chapter3/section3.ipynb"},{label:"Aws Studio",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/hi/chapter3/section3.ipynb"}]}}),J=new Jl({props:{id:"nvBXf7s7vTI"}}),Ee=new U({props:{code:`from datasets import load_dataset
from transformers import AutoTokenizer, DataCollatorWithPadding

raw_datasets = load_dataset("glue", "mrpc")
checkpoint = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)


def tokenize_function(example):
    return tokenizer(example["sentence1"], example["sentence2"], truncation=True)


tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)`,highlighted:`<span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset
<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer, DataCollatorWithPadding

raw_datasets = load_dataset(<span class="hljs-string">&quot;glue&quot;</span>, <span class="hljs-string">&quot;mrpc&quot;</span>)
checkpoint = <span class="hljs-string">&quot;bert-base-uncased&quot;</span>
tokenizer = AutoTokenizer.from_pretrained(checkpoint)


<span class="hljs-keyword">def</span> <span class="hljs-title function_">tokenize_function</span>(<span class="hljs-params">example</span>):
    <span class="hljs-keyword">return</span> tokenizer(example[<span class="hljs-string">&quot;sentence1&quot;</span>], example[<span class="hljs-string">&quot;sentence2&quot;</span>], truncation=<span class="hljs-literal">True</span>)


tokenized_datasets = raw_datasets.<span class="hljs-built_in">map</span>(tokenize_function, batched=<span class="hljs-literal">True</span>)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)`}}),ve=new U({props:{code:`from transformers import TrainingArguments

training_args = TrainingArguments("test-trainer")`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> TrainingArguments

training_args = TrainingArguments(<span class="hljs-string">&quot;test-trainer&quot;</span>)`}}),ae=new Rl({props:{$$slots:{default:[Vl]},$$scope:{ctx:fe}}}),ke=new U({props:{code:`from transformers import AutoModelForSequenceClassification

model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=2)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModelForSequenceClassification

model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=<span class="hljs-number">2</span>)`}}),Ce=new U({props:{code:`from transformers import Trainer

trainer = Trainer(
    model,
    training_args,
    train_dataset=tokenized_datasets["train"],
    eval_dataset=tokenized_datasets["validation"],
    data_collator=data_collator,
    tokenizer=tokenizer,
)`,highlighted:`<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> Trainer

trainer = Trainer(
    model,
    training_args,
    train_dataset=tokenized_datasets[<span class="hljs-string">&quot;train&quot;</span>],
    eval_dataset=tokenized_datasets[<span class="hljs-string">&quot;validation&quot;</span>],
    data_collator=data_collator,
    tokenizer=tokenizer,
)`}}),be=new U({props:{code:"trainer.train()",highlighted:"trainer.train()"}}),we=new U({props:{code:`predictions = trainer.predict(tokenized_datasets["validation"])
print(predictions.predictions.shape, predictions.label_ids.shape)`,highlighted:`predictions = trainer.predict(tokenized_datasets[<span class="hljs-string">&quot;validation&quot;</span>])
<span class="hljs-built_in">print</span>(predictions.predictions.shape, predictions.label_ids.shape)`}}),De=new U({props:{code:"(408, 2) (408,)",highlighted:'(<span class="hljs-number">408</span>, <span class="hljs-number">2</span>) (<span class="hljs-number">408</span>,)'}}),ge=new U({props:{code:`import numpy as np

preds = np.argmax(predictions.predictions, axis=-1)`,highlighted:`<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np

preds = np.argmax(predictions.predictions, axis=-<span class="hljs-number">1</span>)`}}),Pe=new U({props:{code:`import evaluate

metric = evaluate.load("glue", "mrpc")
metric.compute(predictions=preds, references=predictions.label_ids)`,highlighted:`<span class="hljs-keyword">import</span> evaluate

metric = evaluate.load(<span class="hljs-string">&quot;glue&quot;</span>, <span class="hljs-string">&quot;mrpc&quot;</span>)
metric.compute(predictions=preds, references=predictions.label_ids)`}}),je=new U({props:{code:"{'accuracy': 0.8578431372549019, 'f1': 0.8996539792387542}",highlighted:'{<span class="hljs-string">&#x27;accuracy&#x27;</span>: <span class="hljs-number">0.8578431372549019</span>, <span class="hljs-string">&#x27;f1&#x27;</span>: <span class="hljs-number">0.8996539792387542</span>}'}}),Ae=new U({props:{code:`def compute_metrics(eval_preds):
    metric = evaluate.load("glue", "mrpc")
    logits, labels = eval_preds
    predictions = np.argmax(logits, axis=-1)
    return metric.compute(predictions=predictions, references=labels)`,highlighted:`<span class="hljs-keyword">def</span> <span class="hljs-title function_">compute_metrics</span>(<span class="hljs-params">eval_preds</span>):
    metric = evaluate.load(<span class="hljs-string">&quot;glue&quot;</span>, <span class="hljs-string">&quot;mrpc&quot;</span>)
    logits, labels = eval_preds
    predictions = np.argmax(logits, axis=-<span class="hljs-number">1</span>)
    <span class="hljs-keyword">return</span> metric.compute(predictions=predictions, references=labels)`}}),ze=new U({props:{code:`training_args = TrainingArguments("test-trainer", evaluation_strategy="epoch")
model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=2)

trainer = Trainer(
    model,
    training_args,
    train_dataset=tokenized_datasets["train"],
    eval_dataset=tokenized_datasets["validation"],
    data_collator=data_collator,
    tokenizer=tokenizer,
    compute_metrics=compute_metrics,
)`,highlighted:`training_args = TrainingArguments(<span class="hljs-string">&quot;test-trainer&quot;</span>, evaluation_strategy=<span class="hljs-string">&quot;epoch&quot;</span>)
model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=<span class="hljs-number">2</span>)

trainer = Trainer(
    model,
    training_args,
    train_dataset=tokenized_datasets[<span class="hljs-string">&quot;train&quot;</span>],
    eval_dataset=tokenized_datasets[<span class="hljs-string">&quot;validation&quot;</span>],
    data_collator=data_collator,
    tokenizer=tokenizer,
    compute_metrics=compute_metrics,
)`}}),ye=new U({props:{code:"trainer.train()",highlighted:'trainer.trai<span class="hljs-meta">n</span>()'}}),ie=new Rl({props:{$$slots:{default:[Zl]},$$scope:{ctx:fe}}}),{c(){f=s("meta"),z=p(),$(m.$$.fragment),y=p(),w=s("h1"),u=s("a"),g=s("span"),$(x.$$.fragment),H=p(),ee=s("span"),me=a("\u092E\u0949\u0921\u0932 \u0915\u093F Trainer API \u0915\u0947 \u0938\u093E\u0925"),Y=p(),$(T.$$.fragment),_e=p(),$(J.$$.fragment),ue=p(),S=s("p"),Mr=a("\u{1F917} \u091F\u094D\u0930\u093E\u0928\u094D\u0938\u092B\u093C\u0949\u0930\u094D\u092E\u0930 \u090F\u0915 "),Ye=s("code"),Lr=a("\u091F\u094D\u0930\u0947\u0928\u0930"),Ir=a(" \u0915\u094D\u0932\u093E\u0938 \u092A\u094D\u0930\u0926\u093E\u0928 \u0915\u0930\u0924\u093E \u0939\u0948 \u091C\u093F\u0938\u0938\u0947 \u0906\u092A\u0915\u094B \u0909\u092A\u0932\u092C\u094D\u0927 \u0915\u0930\u093E\u090F \u0917\u090F \u0915\u093F\u0938\u0940 \u092D\u0940 \u092A\u0942\u0930\u094D\u0935-\u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 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\u0938\u092C\u0938\u0947 \u0915\u0920\u093F\u0928 \u0939\u093F\u0938\u094D\u0938\u093E "),Xe=s("code"),Nr=a("Trainer.train()"),Wr=a(" \u0915\u094B \u091A\u0932\u093E\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F \u0935\u093E\u0924\u093E\u0935\u0930\u0923 \u0915\u094B \u0924\u0948\u092F\u093E\u0930 \u0915\u0930\u0928\u0947 \u0915\u0940 \u0938\u0902\u092D\u093E\u0935\u0928\u093E \u0939\u0948, \u0915\u094D\u092F\u094B\u0902\u0915\u093F \u092F\u0939 CPU \u092A\u0930 \u092C\u0939\u0941\u0924 \u0927\u0940\u092E\u0940 \u0917\u0924\u093F \u0938\u0947 \u091A\u0932\u0947\u0917\u093E\u0964 \u092F\u0926\u093F \u0906\u092A\u0915\u0947 \u092A\u093E\u0938 GPU \u0938\u0947\u091F \u0905\u092A \u0928\u0939\u0940\u0902 \u0939\u0948, \u0924\u094B \u0906\u092A "),$e=s("a"),Hr=a("Google Colab"),Yr=a(" \u092A\u0930 \u0928\u093F\u0903\u0936\u0941\u0932\u094D\u0915 GPUs \u092F\u093E TPUs \u0915\u093E \u090F\u0915\u094D\u0938\u0947\u0938 \u092A\u094D\u0930\u093E\u092A\u094D\u0924 \u0915\u0930 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\u0939\u0948:"),Zt=p(),$(Ee.$$.fragment),er=p(),he=s("h3"),Xr=a("\u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923"),tr=p(),F=s("p"),Kr=a("\u0939\u092E\u093E\u0930\u0947 "),Ke=s("code"),Qr=a("\u091F\u094D\u0930\u0947\u0928\u0930"),Vr=a(" \u0915\u094B \u092A\u0930\u093F\u092D\u093E\u0937\u093F\u0924 \u0915\u0930\u0928\u0947 \u0938\u0947 \u092A\u0939\u0932\u0947 \u092A\u0939\u0932\u093E \u0915\u0926\u092E \u0939\u0948 \u090F\u0915 "),Qe=s("code"),Zr=a("TrainingArguments"),ea=a(" \u0915\u094D\u0932\u093E\u0938  \u0915\u094B \u092A\u0930\u093F\u092D\u093E\u0937\u093F\u0924 \u0915\u0930\u0928\u093E \u091C\u093F\u0938\u092E\u0947\u0902 \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0914\u0930 \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928 \u0915\u0947 \u0932\u093F\u090F "),Ve=s("code"),ta=a("\u091F\u094D\u0930\u0947\u0928\u0930"),ra=a(" \u0926\u094D\u0935\u093E\u0930\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u093F\u090F \u091C\u093E\u0928\u0947 \u0935\u093E\u0932\u0947 \u0938\u092D\u0940 \u0939\u093E\u0907\u092A\u0930\u092A\u0948\u0930\u093E\u092E\u0940\u091F\u0930 \u0936\u093E\u092E\u093F\u0932 \u0939\u094B\u0902\u0917\u0947\u0964 \u090F\u0915\u092E\u093E\u0924\u094D\u0930 \u0906\u0930\u094D\u0917\u0942\u092E\u0947\u0928\u094D\u091F \u091C\u094B \u0906\u092A\u0915\u094B \u092A\u094D\u0930\u0926\u093E\u0928 \u0915\u0930\u0928\u093E \u0939\u0948 \u0935\u0939 \u0939\u0948 \u090F\u0915 \u0928\u093F\u0930\u094D\u0926\u0947\u0936\u093F\u0915\u093E \u091C\u0939\u093E\u0902 \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 \u092E\u0949\u0921\u0932 \u0938\u0939\u0947\u091C\u093E \u091C\u093E\u090F\u0917\u093E, \u0938\u093E\u0925 \u0939\u0940 \u0938\u093E\u0925 \u091A\u094C\u0915\u093F\u092F\u094B\u0902 \u0915\u094B \u092D\u0940\u0964 \u092C\u093E\u0915\u0940 \u0938\u092D\u0940 \u0915\u0947 \u0932\u093F\u090F, \u0906\u092A \u0921\u093F\u092B\u093C\u0949\u0932\u094D\u091F \u0930\u0942\u092A \u092E\u0947\u0902 \u091B\u094B\u0921\u093C \u0938\u0915\u0924\u0947 \u0939\u0948\u0902, \u091C\u094B \u090F\u0915 \u092C\u0941\u0928\u093F\u092F\u093E\u0926\u0940 \u092B\u093C\u093E\u0907\u0928-\u091F\u094D\u092F\u0942\u0928\u093F\u0902\u0917 \u0915\u0947 \u0932\u093F\u090F \u092C\u0939\u0941\u0924 \u0905\u091A\u094D\u091B\u0940 \u0924\u0930\u0939 \u0938\u0947 \u0915\u093E\u092E \u0915\u0930\u0928\u093E \u091A\u093E\u0939\u093F\u090F\u0964"),rr=p(),$(ve.$$.fragment),ar=p(),$(ae.$$.fragment),or=p(),X=s("p"),aa=a("\u0926\u0942\u0938\u0930\u093E \u0915\u0926\u092E \u0939\u092E\u093E\u0930\u0947 \u092E\u0949\u0921\u0932 \u0915\u094B \u092A\u0930\u093F\u092D\u093E\u0937\u093F\u0924 \u0915\u0930\u0928\u093E \u0939\u0948\u0964 "),Ue=s("a"),oa=a("\u092A\u093F\u091B\u0932\u0947 \u0905\u0927\u094D\u092F\u093E\u092F"),sa=a(" \u0915\u0940 \u0924\u0930\u0939, \u0939\u092E "),Ze=s("code"),la=a("AutoModelForSequenceClassification"),ia=a(" \u0935\u0930\u094D\u0917 \u0915\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u0930\u0947\u0902\u0917\u0947, \u0926\u094B \u0932\u0947\u092C\u0932 \u0915\u0947 \u0938\u093E\u0925 :"),sr=p(),$(ke.$$.fragment),lr=p(),oe=s("p"),na=a("\u0906\u092A \u0926\u0947\u0916\u0947\u0902\u0917\u0947 \u0915\u093F "),Fe=s("a"),ca=a("\u0905\u0927\u094D\u092F\u093E\u092F 2"),pa=a(" \u0915\u0947 \u0935\u093F\u092A\u0930\u0940\u0924, \u0906\u092A\u0915\u094B \u0907\u0938 \u092A\u0942\u0930\u094D\u0935-\u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 \u092E\u0949\u0921\u0932 \u0915\u094B \u0907\u0928\u094D\u0938\u094D\u091F\u0948\u0928\u094D\u0936\u0940\u0910\u091F \u0915\u0930\u0928\u0947 \u0915\u0947 \u092C\u093E\u0926 \u090F\u0915 \u091A\u0947\u0924\u093E\u0935\u0928\u0940 \u092E\u093F\u0932\u0924\u0940 \u0939\u0948\u0964 \u0910\u0938\u093E \u0907\u0938\u0932\u093F\u090F \u0939\u0948 \u0915\u094D\u092F\u094B\u0902\u0915\u093F BERT \u0915\u094B \u0935\u093E\u0915\u094D\u092F\u094B\u0902 \u0915\u0947 \u091C\u094B\u0921\u093C\u0947 \u0915\u093E \u0935\u0930\u094D\u0917\u0940\u0915\u0930\u0923 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F \u092A\u0942\u0930\u094D\u0935 \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 \u0928\u0939\u0940\u0902 \u0915\u093F\u092F\u093E \u0917\u092F\u093E \u0939\u0948, \u0907\u0938\u0932\u093F\u090F \u092A\u0942\u0930\u094D\u0935-\u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 \u092E\u0949\u0921\u0932 \u0915\u0947 \u092A\u094D\u0930\u092E\u0941\u0916 \u0915\u094B \u0924\u094D\u092F\u093E\u0917 \u0926\u093F\u092F\u093E \u0917\u092F\u093E \u0939\u0948 \u0914\u0930 \u0907\u0938\u0915\u0947 \u092C\u091C\u093E\u092F\u0947 \u0905\u0928\u0941\u0915\u094D\u0930\u092E \u0935\u0930\u094D\u0917\u0940\u0915\u0930\u0923 \u0915\u0947 \u0932\u093F\u090F \u0909\u092A\u092F\u0941\u0915\u094D\u0924 \u090F\u0915 \u0928\u092F\u093E \u092A\u094D\u0930\u092E\u0941\u0916 \u0921\u093E\u0932\u093E \u0917\u092F\u093E \u0939\u0948\u0964 \u0907\u0928 \u091A\u0947\u0924\u093E\u0935\u0928\u093F\u092F\u094B\u0902 \u0938\u0947 \u0938\u0902\u0915\u0947\u0924 \u092E\u093F\u0932\u0924\u093E \u0939\u0948 \u0915\u093F \u0915\u0941\u091B \u0935\u091C\u093C\u0928 \u0915\u093E \u0909\u092A\u092F\u094B\u0917 \u0928\u0939\u0940\u0902 \u0915\u093F\u092F\u093E \u0917\u092F\u093E \u0925\u093E (\u0924\u094D\u092F\u093E\u0917\u0947 \u0917\u090F \u092A\u0942\u0930\u094D\u0935-\u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0915\u0947 \u092A\u094D\u0930\u092E\u0941\u0916 \u0915\u0947 \u0905\u0928\u0941\u0930\u0942\u092A) \u0914\u0930 \u0915\u0941\u091B \u0905\u0928\u094D\u092F \u0915\u094D\u0930\u092E\u0930\u0939\u093F\u0924 \u0930\u0942\u092A \u0938\u0947 \u092A\u094D\u0930\u093E\u0930\u0902\u092D \u0915\u093F\u090F \u0917\u090F \u0925\u0947 (\u0928\u090F \u092A\u094D\u0930\u092E\u0941\u0916 \u0915\u0947 \u0932\u093F\u090F \u0935\u093E\u0932\u0947)\u0964 \u092F\u0939 \u0938\u092E\u093E\u092A\u0928 \u0906\u092A\u0915\u094B \u092E\u0949\u0921\u0932 \u0915\u094B \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u093F\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F \u092A\u094D\u0930\u094B\u0924\u094D\u0938\u093E\u0939\u093F\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0938\u093E\u0925 \u0939\u094B\u0917\u093E, \u091C\u094B \u0915\u093F \u0905\u092C \u0939\u092E \u0915\u0930\u0928\u0947 \u091C\u093E \u0930\u0939\u0947 \u0939\u0948\u0902\u0964"),ir=p(),O=s("p"),da=a("\u090F\u0915 \u092C\u093E\u0930 \u091C\u092C \u0939\u092E\u093E\u0930\u0947 \u092A\u093E\u0938 \u0939\u092E\u093E\u0930\u093E \u092E\u0949\u0921\u0932 \u0939\u094B\u0917\u093E, \u0924\u094B \u0939\u092E \u090F\u0915 "),et=s("code"),fa=a("Trainer"),ma=a(" \u0915\u094B \u092A\u0930\u093F\u092D\u093E\u0937\u093F\u0924 \u0905\u092C \u0924\u0915 \u0915\u0940 \u0928\u093F\u0930\u094D\u092E\u093F\u0924 \u0938\u092D\u0940 \u0935\u0938\u094D\u0924\u0941\u0913\u0902 \u0915\u094B \u092A\u093E\u0938 \u0915\u0930\u0915\u0947 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948 \u2014 "),tt=s("code"),_a=a("model"),ua=a(", "),rt=s("code"),$a=a("training_args"),Ea=a(", \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0914\u0930 \u0938\u0924\u094D\u092F\u093E\u092A\u0928 \u0921\u0947\u091F\u093E\u0938\u0947\u091F, \u0939\u092E\u093E\u0930\u0947 "),at=s("code"),ha=a("data_collator"),va=a(", \u0914\u0930 \u0939\u092E\u093E\u0930\u0947 "),ot=s("code"),ka=a("tokenizer"),Ca=a(":"),nr=p(),$(Ce.$$.fragment),cr=p(),P=s("p"),ba=a("\u0927\u094D\u092F\u093E\u0928 \u0926\u0947\u0902 \u0915\u093F \u091C\u092C \u0906\u092A "),st=s("code"),Ta=a("tokenizer"),wa=a(" \u092A\u093E\u0938 \u0915\u0930\u0924\u0947 \u0939\u0948\u0902 \u091C\u0948\u0938\u093E \u0915\u093F \u0939\u092E\u0928\u0947 \u092F\u0939\u093E\u0902 \u0915\u093F\u092F\u093E \u0925\u093E, \u0924\u094B "),lt=s("code"),Da=a("Trainer"),ga=a(" \u0926\u094D\u0935\u093E\u0930\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u093F\u092F\u093E \u091C\u093E\u0928\u0947 \u0935\u093E\u0932\u093E \u0921\u093F\u092B\u093C\u0949\u0932\u094D\u091F "),it=s("code"),Oa=a("data_colllator"),Pa=a(" \u090F\u0915 "),nt=s("code"),ja=a("DataCollatorWithPadding"),qa=a(" \u0939\u094B\u0917\u093E \u091C\u0948\u0938\u093E \u0915\u093F \u092A\u0939\u0932\u0947 \u092A\u0930\u093F\u092D\u093E\u0937\u093F\u0924 \u0915\u093F\u092F\u093E \u0917\u092F\u093E \u0925\u093E, \u0907\u0938\u0932\u093F\u090F \u0906\u092A \u0907\u0938 \u0915\u0949\u0932 \u092E\u0947\u0902 "),ct=s("code"),Aa=a("data_collator=data_collator"),za=a(" \u0932\u093E\u0907\u0928 \u0915\u094B \u091B\u094B\u0921\u093C \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0906\u092A\u0915\u094B \u092A\u094D\u0930\u094B\u0938\u0947\u0938\u093F\u0902\u0917 \u0915\u0947 \u0907\u0938 \u092D\u093E\u0917 \u0915\u094B \u0916\u0902\u0921 2 \u092E\u0947\u0902 \u0926\u093F\u0916\u093E\u0928\u093E \u092B\u093F\u0930 \u092D\u0940 \u092E\u0939\u0924\u094D\u0935\u092A\u0942\u0930\u094D\u0923 \u0925\u093E!"),pr=p(),K=s("p"),ya=a("\u092E\u0949\u0921\u0932 \u0915\u094B \u0939\u092E\u093E\u0930\u0947 \u0921\u0947\u091F\u093E\u0938\u0947\u091F \u092A\u0930 \u092B\u093E\u0907\u0928-\u091F\u094D\u092F\u0942\u0928 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F, \u0939\u092E\u0947\u0902 \u092C\u0938 \u0905\u092A\u0928\u0947 "),pt=s("code"),xa=a("Trainer"),Sa=a(" \u0915\u0947 "),dt=s("code"),Ua=a("train()"),Fa=a(" \u0935\u093F\u0927\u093F \u0915\u094B \u0915\u0949\u0932 \u0915\u0930\u0928\u093E \u0939\u094B\u0917\u093E:"),dr=p(),$(be.$$.fragment),fr=p(),Ge=s("p"),Ga=a("\u092F\u0939 \u092B\u093E\u0907\u0928-\u091F\u094D\u092F\u0942\u0928\u093F\u0902\u0917 \u0915\u094B \u0936\u0941\u0930\u0942 \u0915\u0930\u0947\u0917\u093E (\u091C\u093F\u0938\u092E\u0947\u0902 GPU \u092A\u0930 \u0915\u0941\u091B \u092E\u093F\u0928\u091F \u0932\u0917\u0928\u0947 \u091A\u093E\u0939\u093F\u090F) \u0914\u0930 \u0939\u0930 500 \u0915\u0926\u092E \u092A\u0930 \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0932\u0949\u0938 \u0915\u0940 \u0930\u093F\u092A\u094B\u0930\u094D\u091F \u0915\u0930\u0947\u0917\u093E \u0964 \u0939\u093E\u0932\u093E\u0902\u0915\u093F, \u092F\u0939 \u0906\u092A\u0915\u094B \u092F\u0939 \u0928\u0939\u0940\u0902 \u092C\u0924\u093E\u090F\u0917\u093E \u0915\u093F \u0906\u092A\u0915\u093E \u092E\u0949\u0921\u0932 \u0915\u093F\u0924\u0928\u093E \u0905\u091A\u094D\u091B\u093E (\u092F\u093E \u0916\u0930\u093E\u092C) \u092A\u094D\u0930\u0926\u0930\u094D\u0936\u0928 \u0915\u0930 \u0930\u0939\u093E \u0939\u0948\u0964 \u092F\u0939 \u0939\u0948 \u0915\u094D\u092F\u094B\u0902\u0915\u093F:"),mr=p(),se=s("ol"),A=s("li"),Ma=a("\u0939\u092E\u0928\u0947 "),ft=s("code"),La=a("Trainer"),Ia=a(" \u0915\u094B \u0928\u0939\u0940\u0902 \u092C\u0924\u093E\u092F\u093E \u0915\u0940 \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0915\u0947 \u0926\u094C\u0930\u093E\u0928 \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F  "),mt=s("code"),Ra=a("evaluation_strategy"),Ba=a(" \u0915\u094B \u092F\u093E \u0924\u094B "),_t=s("code"),Na=a('"steps"'),Wa=a("(\u0939\u0930 "),ut=s("code"),Ha=a("eval_steps"),Ya=a(" \u0915\u093E \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928 \u0915\u0930\u0947\u0902) \u092F\u093E "),$t=s("code"),Ja=a('"epoch"'),Xa=a(" (\u092A\u094D\u0930\u0924\u094D\u092F\u0947\u0915 \u090F\u092A\u0949\u0915 \u0915\u0947 \u0905\u0902\u0924 \u092E\u0947\u0902 \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928) \u0915\u094B \u0938\u0947\u091F \u0915\u0930\u0947\u0964"),Ka=p(),te=s("li"),Qa=a("\u0939\u092E\u0928\u0947 "),Et=s("code"),Va=a("Trainer"),Za=a(" \u0915\u094B "),ht=s("code"),eo=a("compute_metrics()"),to=a(" \u092B\u093C\u0902\u0915\u094D\u0936\u0928 \u0915\u0947 \u0938\u093E\u0925 \u092A\u094D\u0930\u0926\u093E\u0928 \u0928\u0939\u0940\u0902 \u0915\u093F\u092F\u093E \u091C\u094B \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928 \u0915\u0947 \u0926\u094C\u0930\u093E\u0928 \u092E\u0940\u091F\u094D\u0930\u093F\u0915 \u0915\u0940 \u0917\u0923\u0928\u093E \u0915\u0930\u0924\u093E \u0939\u0948 (\u0905\u0928\u094D\u092F\u0925\u093E \u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928 \u0928\u0947 \u0915\u0947\u0935\u0932 \u0932\u0949\u0938 \u0915\u094B \u092E\u0941\u0926\u094D\u0930\u093F\u0924 \u0915\u093F\u092F\u093E \u0939\u094B\u0917\u093E, \u091C\u094B \u092C\u0939\u0941\u0924 \u0938\u0939\u091C \u0938\u0902\u0916\u094D\u092F\u093E \u0928\u0939\u0940\u0902 \u0939\u0948)"),_r=p(),Te=s("h3"),ro=a("\u092E\u0942\u0932\u094D\u092F\u093E\u0902\u0915\u0928"),ur=p(),j=s("p"),ao=a("\u0906\u0907\u090F \u0926\u0947\u0916\u0947\u0902 \u0915\u093F \u0939\u092E \u090F\u0915 \u0909\u092A\u092F\u094B\u0917\u0940 "),vt=s("code"),oo=a("compute_metrics()"),so=a(" \u092B\u093C\u0902\u0915\u094D\u0936\u0928 \u0915\u0948\u0938\u0947 \u092C\u0928\u093E \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0914\u0930 \u0905\u0917\u0932\u0940 \u092C\u093E\u0930 \u091C\u092C \u0939\u092E \u092A\u094D\u0930\u0936\u093F\u0915\u094D\u0937\u0923 \u0915\u0930\u0947\u0902\u0917\u0947 \u0924\u094B \u0907\u0938\u0915\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u0948\u0938\u0947 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u092B\u093C\u0902\u0915\u094D\u0936\u0928 \u0915\u094B \u090F\u0915 "),kt=s("code"),lo=a("EvalPrediction"),io=a(" \u0911\u092C\u094D\u091C\u0947\u0915\u094D\u091F \u0932\u0947\u0928\u093E \u0939\u094B\u0917\u093E (\u091C\u094B \u090F\u0915 "),Ct=s("code"),no=a("predictions"),co=a(" \u092B\u093C\u0940\u0932\u094D\u0921 \u0914\u0930 \u090F\u0915 "),bt=s("code"),po=a("label_ids"),fo=a(" \u092B\u093C\u0940\u0932\u094D\u0921 \u0915\u0947 \u0938\u093E\u0925 \u090F\u0915 \u0928\u093E\u092E\u093F\u0924 \u091F\u092A\u0932 \u0939\u0948) \u0914\u0930 \u0932\u094C\u091F\u093E\u090F\u0917\u093E \u090F\u0915 \u0921\u093F\u0915\u094D\u0936\u0928\u0930\u0940 \u091C\u094B \u092E\u0948\u092A \u0915\u0930\u0947\u0917\u093E \u0938\u094D\u091F\u094D\u0930\u093F\u0902\u0917\u094D\u0938 \u0915\u094B \u092B\u093C\u094D\u0932\u094B\u091F \u092E\u0947\u0902 (\u0938\u094D\u091F\u094D\u0930\u093F\u0902\u0917\u094D\u0938 \u0932\u094C\u091F\u093E\u090F \u0917\u090F \u092E\u0947\u091F\u094D\u0930\u093F\u0915\u094D\u0938 \u0915\u0947 \u0928\u093E\u092E \u0939\u0948\u0902, \u0914\u0930 \u092B\u093C\u094D\u0932\u094B\u091F \u0909\u0928\u0915\u0940 \u0935\u0948\u0932\u094D\u092F\u0942\u091C)\u0964 \u0939\u092E\u093E\u0930\u0947 \u092E\u0949\u0921\u0932 \u0938\u0947 \u0915\u0941\u091B \u092A\u094D\u0930\u093F\u0921\u093F\u0915\u094D\u0936\u0928\u094D\u0938 \u092A\u094D\u0930\u093E\u092A\u094D\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F, \u0939\u092E "),Tt=s("code"),mo=a("Trainer.predict()"),_o=a(" \u0915\u092E\u093E\u0902\u0921 \u0915\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:"),$r=p(),$(we.$$.fragment),Er=p(),$(De.$$.fragment),hr=p(),_=s("p"),wt=s("code"),uo=a("predict()"),$o=a(" \u0935\u093F\u0927\u093F \u0915\u093E \u0906\u0909\u091F\u092A\u0941\u091F \u0928\u093E\u092E\u093F\u0924 \u091F\u092A\u0932 \u0939\u0948 \u0924\u0940\u0928 \u0915\u094D\u0937\u0947\u0924\u094D\u0930\u094B\u0902 \u0915\u0947 \u0938\u093E\u0925 : "),Dt=s("code"),Eo=a("predictions"),ho=a(", "),gt=s("code"),vo=a("label_ids"),ko=a(", \u0914\u0930 "),Ot=s("code"),Co=a("metrics"),bo=a("\u0964 "),Pt=s("code"),To=a("metrics"),wo=a(" \u092B\u093C\u0940\u0932\u094D\u0921 \u092E\u0947\u0902 \u0915\u0947\u0935\u0932 \u092A\u093E\u0938 \u0915\u093F\u090F \u0917\u090F \u0921\u0947\u091F\u093E\u0938\u0947\u091F \u092A\u0930 \u0939\u094B\u0928\u0947 \u0935\u093E\u0932\u093E \u0932\u0949\u0938 \u0939\u094B\u0917\u093E, \u0938\u093E\u0925 \u0939\u0940 \u0938\u093E\u0925 \u0915\u0941\u091B \u0938\u092E\u092F \u092E\u0940\u091F\u094D\u0930\u093F\u0915 (\u0915\u0941\u0932 \u0914\u0930 \u0914\u0938\u0924 \u0930\u0942\u092A \u0938\u0947 \u092A\u094D\u0930\u093F\u0921\u093F\u0915\u094D\u091F \u0915\u0930\u0928\u0947 \u092E\u0947\u0902 \u0915\u093F\u0924\u0928\u093E \u0938\u092E\u092F \u0932\u0917\u093E) \u0936\u093E\u092E\u093F\u0932 \u0939\u094B\u0902\u0917\u0947\u0964 \u090F\u0915 \u092C\u093E\u0930 \u091C\u092C \u0939\u092E \u0905\u092A\u0928\u093E "),jt=s("code"),Do=a("compute_metrics()"),go=a(" \u092B\u093C\u0902\u0915\u094D\u0936\u0928 \u092A\u0942\u0930\u093E \u0915\u0930 \u0932\u0947\u0924\u0947 \u0939\u0948\u0902 \u0914\u0930 \u0907\u0938\u0947 "),qt=s("code"),Oo=a("\u091F\u094D\u0930\u0947\u0928\u0930"),Po=a(" \u0915\u094B \u092A\u093E\u0938 \u0915\u0930 \u0926\u0947\u0924\u0947 \u0939\u0948\u0902, \u0924\u094B \u0909\u0938 \u092B\u093C\u0940\u0932\u094D\u0921 \u092E\u0947\u0902 "),At=s("code"),jo=a("compute_metrics()"),qo=a(" \u0926\u094D\u0935\u093E\u0930\u093E \u0932\u094C\u091F\u093E\u090F \u0917\u090F \u092E\u0940\u091F\u094D\u0930\u093F\u0915 \u092D\u0940 \u0936\u093E\u092E\u093F\u0932 \u0939\u094B\u0902\u0917\u0947\u0964"),vr=p(),G=s("p"),Ao=a("\u091C\u0948\u0938\u093E \u0915\u093F \u0906\u092A \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902, "),zt=s("code"),zo=a("predictions"),yo=a(" \u090F\u0915 2-\u0921\u093F\u092E\u0947\u0928\u094D\u0936\u0928\u0932 \u0938\u0930\u0923\u0940 \u0939\u0948 \u091C\u093F\u0938\u0915\u093E \u0906\u0915\u093E\u0930 408 x 2 (408 \u0939\u092E\u093E\u0930\u0947 \u0926\u094D\u0935\u093E\u0930\u093E \u0909\u092A\u092F\u094B\u0917 \u0915\u093F\u090F \u0917\u090F \u0921\u0947\u091F\u093E\u0938\u0947\u091F \u092E\u0947\u0902 \u0924\u0924\u094D\u0935\u094B\u0902 \u0915\u0940 \u0938\u0902\u0916\u094D\u092F\u093E \u0939\u0948)\u0964 \u0935\u0947 \u0921\u0947\u091F\u093E\u0938\u0947\u091F \u0915\u0947 \u092A\u094D\u0930\u0924\u094D\u092F\u0947\u0915 \u0924\u0924\u094D\u0935 \u0915\u0947 \u0932\u093F\u090F \u0932\u0949\u0917\u093F\u091F \u0939\u0948\u0902 \u091C\u093F\u0928\u094D\u0939\u0947\u0902 \u0939\u092E\u0928\u0947 "),yt=s("code"),xo=a("predict()"),So=a(" \u092E\u0947\u0902 \u092A\u093E\u0938 \u0915\u093F\u092F\u093E \u0939\u0948 (\u091C\u0948\u0938\u093E \u0915\u093F \u0906\u092A\u0928\u0947 "),Me=s("a"),Uo=a("\u092A\u093F\u091B\u0932\u0947 \u0905\u0927\u094D\u092F\u093E\u092F"),Fo=a(" \u092E\u0947\u0902 \u0926\u0947\u0916\u093E \u0925\u093E, \u0938\u092D\u0940 \u091F\u094D\u0930\u093E\u0902\u0938\u092B\u0949\u0930\u094D\u092E\u0930 \u092E\u0949\u0921\u0932 \u0932\u0949\u0917\u093F\u091F \u0932\u094C\u091F\u093E\u0924\u0947 \u0939\u0948\u0902)\u0964 \u0909\u0928\u094D\u0939\u0947\u0902 \u092D\u0935\u093F\u0937\u094D\u092F\u0935\u093E\u0923\u093F\u092F\u094B\u0902 \u092F\u093E\u0928\u093F \u092A\u094D\u0930\u093F\u0921\u093F\u0915\u094D\u0936\u0928\u094D\u0938 \u092E\u0947\u0902 \u092C\u0926\u0932\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F \u091C\u093F\u0928\u094D\u0939\u0947\u0902 \u0939\u092E \u0905\u092A\u0928\u0947 \u0932\u0947\u092C\u0932 \u0938\u0947 \u0924\u0941\u0932\u0928\u093E \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902, \u0939\u092E\u0947\u0902 \u0926\u0942\u0938\u0930\u0940 \u090F\u0915\u094D\u0938\u093F\u0938 \u092A\u0930 \u0905\u0927\u093F\u0915\u0924\u092E \u092E\u0942\u0932\u094D\u092F \u0915\u0947 \u0938\u093E\u0925 \u0907\u0928\u094D\u0921\u0947\u0915\u094D\u0938 \u0932\u0947\u0928\u0947 \u0915\u0940 \u0906\u0935\u0936\u094D\u092F\u0915\u0924\u093E \u0939\u0948:"),kr=p(),$(ge.$$.fragment),Cr=p(),q=s("p"),Go=a("\u0905\u092C \u0939\u092E \u0909\u0928 "),xt=s("code"),Mo=a("preds"),Lo=a(" \u0915\u0940 \u0924\u0941\u0932\u0928\u093E \u0932\u0947\u092C\u0932 \u0938\u0947 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0939\u092E\u093E\u0930\u0947 "),St=s("code"),Io=a("compute_metric()"),Ro=a(" \u092B\u093C\u0902\u0915\u094D\u0936\u0928 \u0915\u094B \u092C\u0928\u093E\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F, \u0939\u092E \u{1F917} 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\u0907\u0938\u0928\u0947 \u090F\u0915 \u0935\u0938\u094D\u0924\u0941 \u0932\u094C\u091F\u093E\u092F\u093E \u091C\u093F\u0938\u092E\u0947 \u090F\u0915 "),Ft=s("code"),Yo=a("compute()"),Jo=a(" \u0935\u093F\u0927\u093F \u0939\u0948 \u091C\u093F\u0938\u0915\u093E \u0909\u092A\u092F\u094B\u0917 \u0939\u092E \u092E\u0940\u091F\u094D\u0930\u093F\u0915 \u0917\u0923\u0928\u093E \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093F\u090F \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:"),br=p(),$(Pe.$$.fragment),Tr=p(),$(je.$$.fragment),wr=p(),M=s("p"),Xo=a("\u0906\u092A\u0915\u094B \u092E\u093F\u0932\u0928\u0947 \u0935\u093E\u0932\u0947 \u0938\u091F\u0940\u0915 \u092A\u0930\u093F\u0923\u093E\u092E \u0905\u0932\u0917-\u0905\u0932\u0917 \u0939\u094B \u0938\u0915\u0924\u0947 \u0939\u0948\u0902, \u0915\u094D\u092F\u094B\u0902\u0915\u093F \u092E\u0949\u0921\u0932 \u0939\u0947\u0921 \u0915\u0947 \u0915\u094D\u0930\u092E\u0930\u0939\u093F\u0924 \u0907\u0928\u093F\u0936\u093F\u092F\u0932\u093E\u0907\u091C\u093C\u0947\u0936\u0928 \u0938\u0947 \u092A\u094D\u0930\u093E\u092A\u094D\u0924 \u092E\u0947\u091F\u094D\u0930\u093F\u0915\u094D\u0938 \u092E\u0947\u0902 \u092C\u0926\u0932\u093E\u0935 \u0939\u094B \u0938\u0915\u0924\u093E \u0939\u0948\u0964 \u092F\u0939\u093E\u0902, \u0939\u092E \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0915\u093F \u0939\u092E\u093E\u0930\u0947 \u092E\u0949\u0921\u0932 \u0915\u093E \u0938\u0924\u094D\u092F\u093E\u092A\u0928 \u0938\u0947\u091F \u092A\u0930 85.78% \u0915\u0940 \u0938\u091F\u0940\u0915\u0924\u093E \u0939\u0948 \u0914\u0930 89.97 \u0915\u093E F1 \u0938\u094D\u0915\u094B\u0930 \u0939\u0948\u0964 \u0935\u0947 \u0926\u094B  \u092E\u0947\u091F\u094D\u0930\u093F\u0915\u094D\u0938 \u0939\u0948\u0902 \u091C\u093F\u0928\u0915\u093E \u0909\u092A\u092F\u094B\u0917 GLUE \u092C\u0947\u0902\u091A\u092E\u093E\u0930\u094D\u0915 \u0915\u0947 \u0932\u093F\u090F MRPC 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