SentenceTransformer based on microsoft/graphcodebert-base

This is a sentence-transformers model finetuned from microsoft/graphcodebert-base. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

Model Type: Sentence Transformer
Base model: microsoft/graphcodebert-base
Maximum Sequence Length: 512 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Cosine Similarity

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'RobertaModel'})
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("buelfhood/SOCO-C-GraphCodeBERT-ST")
# Run inference
sentences = [
    '#include<stdio.h>\n#include<stdlib.h>\n\nint ()\n{\n\nFILE *fin1;\nFILE *fin2;\nint flag=0;\n\n\nwhile(1)\n{\n    \n        system("wget -p http://www.cs.rmit.edu./students");\n\n        system("cd www.cs.rmit.edu./");\n\n    \n    \n   if(flag>0)\n   {\n    \n    fin1=fopen("./watchtext/index.html","r");\n    fin2=fopen("./watchtext/test2.txt","r");\n    system("diff ./www.cs.rmit.edu./students/index.html ./watchtext/index.html | mail @cs.rmit.edu.");\n    system("cp ./www.cs.rmit.edu./students/index.html ./watchtext/index.html ");\n    system("md5sum ./www.cs.rmit.edu./images/*.* > ./www.cs.rmit.edu./test2.txt");\n    system("diff ./www.cs.rmit.edu./test2.txt ./watchtext/test2.txt | mail @cs.rmit.edu.");\n    system("cp ./www.cs.rmit.edu./test2.txt ./watchtext/test2.txt");\n    system("rm ./www.cs.rmit.edu./test2.txt");\n           \n    fclose(fin2);\n    fclose(fin1);   \n   }    \n  \n    if(flag==0)\n    {\n     system("mkdir watchtext");     \n     if((fin1=fopen("./watchtext/index.html","r"))==NULL)\n     {\n      system("cp ./www.cs.rmit.edu./students/index.html ./watchtext/index.html");\n      system("md5sum ./www.cs.rmit.edu./images/*.* > ./watchtext/test2.txt");\n      \n      flag++;\n      }\n     \n   } \n    \n  \n  \n   printf("Running every 24 hours");     \n  sleep(86400); \n  \n}\n system("rmdir ./watchtext");      \n}       \n       \n       \n       \n       \n',
    '#include<stdio.h>\n#include<stdlib.h>\n#include<string.h> \n#include <ctype.h>\n#include <sys/time.h>\n\n\n#define SUCCESS 0;\n#define FAILURE 1;\n#define SECONDS 1e9\n\nint findPassword(char *);\nint smallPass();\nint capsPass();\n\nint main()\n{\n\tint foundP;\t\n\tfoundP=smallPass();\n\tfoundP=capsPass();\n\tif(foundP == 2)\n\t{\t\t\n\t\treturn SUCCESS;\n\t}\n\tprintf("\\n PASSWORD NOT FOUND");\n\treturn SUCCESS;\n  \n}\n\nint smallPass()\n{\n\tchar [26] ={\'a\',\'b\',\'c\',\'d\',\'e\',\'f\',\'g\',\'h\',\'i\',\'j\',\'k\',\'l\',\'m\',\'n\',\'o\',\'p\',\'q\',\'r\',\'s\',\'t\',\'u\',\'v\',\'w\',\'x\',\'y\',\'z\'};\t\n\tchar pass[3]="";\t\n\tint i,j,k,l;\n\tint incr;\n\tint found;\n\tint , end, final;\t\n\t\n\t = time();\n\tfor(j=0;j<3;j++)\n\t{\n\t\tincr=0;\t\t\n\t\tfor(i=0;i<=25;i++)\n\t\t{\t\t\t\t\n\t\t\tif(j==0)\n\t\t\t{\t\n\t\t\t\tincr++;\n\t\t\t\tpass[j]=[i];\n\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\tfound = findPassword(pass);\n\t\t\t\tif(found == 2)\n\t\t\t\t{\t\n\t\t\t\t\tend = time();\n\t\t\t\t\tfinal = end-;\n\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\n\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\t\n\t\t\t\t\treturn 2;\n\t\t\t\t}\n\t\t\t\t\n\t\t\t}\n\t\t\tif(j==1)\n\t\t\t{\t\t\t\t\n\t\t\t\tpass[j-1]=[i];\n\t\t\t\tfor(k=0;k<=25;k++)\n\t\t\t\t{\n\t\t\t\t\tincr++;\n\t\t\t\t\tpass[j] = [k];\n\t\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\t\tfound = findPassword(pass);\n\t\t\t\t\tif(found == 2)\n\t\t\t\t\t{\t\n\t\t\t\t\t\tend = time();\n\t\t\t\t\t\tfinal = end-;\n\t\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\n\t\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\n\t\t\t\t\t\treturn 2;\n\t\t\t\t\t}\t\n\t\t\t\t}\n\t\t\t}\n\t\t\tif(j==2)\n\t\t\t{\t\t\t\t\t\t\n\t\t\t\tpass[j-2]=[i];\n\t\t\t\tfor(k=0;k<=25;k++)\n\t\t\t\t{\n\t\t\t\t\tpass[j-1] = [k];\n\t\t\t\t\tfor(l=0;l<=25;l++)\n\t\t\t\t\t{\n\t\t\t\t\t\tincr++;\n\t\t\t\t\t\tpass[j] = [l];\n\t\t\t\t\t\tpass[j+1]=\'\\0\';\n\t\t\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\t\t\tfound = findPassword(pass);\n\t\t\t\t\t\tif(found == 2)\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\tend = time();\n\t\t\t\t\t\t\tfinal = end-;\n\t\t\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\t\t\t\t\t\n\t\t\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\t\t\t\n\t\t\t\t\t\t\treturn 2;\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\n\t\t\t\t}\n\t\t\t}\t\t\n\t\t\t\n\t\t\t\n\t\t}\n\t}\n\t\n\treturn SUCCESS;\t\n}\n\n\n\nint capsPass()\n{\n\tchar caps[26] ={\'A\',\'B\',\'C\',\'D\',\'E\',\'F\',\'G\',\'H\',\'I\',\'J\',\'K\',\'L\',\'M\',\'N\',\'O\',\'P\',\'Q\',\'R\',\'S\',\'T\',\'U\',\'V\',\'W\',\'X\',\'Y\',\'Z\'};\t\n\tchar pass[3]="";\t\n\tint i,j,k,l;\n\tint incr;\n\tint found;\n\tint , end, final;\t\n\t\n\t = time();\n\tfor(j=2;j<3;j++)\n\t{\n\t\tincr=0;\n\t\tfor(i=0;i<=25;i++)\n\t\t{\n\t\t\t\t\n\t\t\tif(j==0)\n\t\t\t{\t\n\t\t\t\tincr++;\n\t\t\t\tpass[j]=caps[i];\n\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\tfound = findPassword(pass);\n\t\t\t\tif(found == 2)\n\t\t\t\t{\t\n\t\t\t\t\tend = time();\n\t\t\t\t\tfinal = end-;\n\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\n\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\t\n\t\t\t\t\treturn 2;\n\t\t\t\t}\n\t\t\t\t\n\t\t\t}\n\t\t\tif(j==1)\n\t\t\t{\t\t\t\t\n\t\t\t\tpass[j-1]=caps[i];\n\t\t\t\tfor(k=0;k<=25;k++)\n\t\t\t\t{\n\t\t\t\t\tincr++;\n\t\t\t\t\tpass[j] = caps[k];\n\t\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\t\tfound = findPassword(pass);\n\t\t\t\t\tif(found == 2)\n\t\t\t\t\t{\t\n\t\t\t\t\t\tend = time();\n\t\t\t\t\t\tfinal = end-;\n\t\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\n\t\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\n\t\t\t\t\t\treturn 2;\n\t\t\t\t\t}\t\n\t\t\t\t}\n\t\t\t}\n\t\t\tif(j==2)\n\t\t\t{\t\t\t\t\n\t\t\t\tpass[j-2]=caps[i];\n\t\t\t\tfor(k=0;k<=25;k++)\n\t\t\t\t{\n\t\t\t\t\tpass[j-1] = caps[k];\n\t\t\t\t\tfor(l=0;l<=25;l++)\n\t\t\t\t\t{\n\t\t\t\t\t\tincr++;\n\t\t\t\t\t\tpass[j] = caps[l];\n\t\t\t\t\t\tpass[j+1]=\'\\0\';\n\t\t\t\t\t\tprintf("\\n Trial  %d  ---  %s ",incr,pass);\n\t\t\t\t\t\tfound = findPassword(pass);\n\t\t\t\t\t\tif(found == 2)\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\tend = time();\n\t\t\t\t\t\t\tfinal = end-;\n\t\t\t\t\t\t\tprintf(" %lld nanoseconds (%1f seconds)  find the Password\\n",final,(double) final / SECONDS);\n\t\t\t\t\t\t\tprintf("\\nPASSWORD FOUND   --   %s",pass);\t\t\t\t\t\t\n\t\t\t\t\t\t\treturn 2;\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\n\t\t\t\t}\n\t\t\t}\t\t\n\t\t\t\n\t\t\t\n\t\t}\n\t}\n\t\n\treturn SUCCESS;\t\n}\n\n\nint findPassword(char *pass)\n{\n\tchar var[50]="";\t\n\tchar [50]="";\n\tstrcpy(var,"wget --non-verbose --http-user= --http-passwd=");\t\t\n\tstrcpy(," http://sec-crack.cs.rmit.edu./SEC/2/index.php");\n\tstrcat(var,pass);\n\tstrcat(var,);\n\tif(system(var)==0)\n\t{\t\t\n\t\treturn 2;\n\t}\t\n\t\t\n\treturn SUCCESS;\n}\n\n\n\t \n',
    '#include<stdio.h>\n#include<string.h>\n#include<strings.h>\n#include<stdlib.h>\n#include<sys/time.h>\n\n()\n{\n\tint i,j,k,m,count=0,flage=0;\n\tFILE* log;\n\ttime_t ,finish;\n\tdouble ttime;\n\tchar s[30];\n\tchar arr[52]={\'a\',\'b\',\'c\',\'d\',\'e\',\'f\',\'g\',\'h\',\'i\',\'j\',\'k\',\'l\',\'m\',\'n\',\'o\',\'p\',\'q\',\'r\',\'s\',\'t\',\'u\',\'v\',\'w\',\'x\',\'y\',\'z\',\'A\',\'B\',\'C\',\'D\',\'E\',\'F\',\'G\',\'H\',\'I\',\'J\',\'K\',\'L\',\'M\',\'N\',\'O\',\'P\',\'Q\',\'R\',\'S\',\'T\',\'U\',\'V\',\'W\',\'X\',\'Y\',\'Z\'};\n\tchar add[100];\n\tstrcpy(add,"wget --http-user= --http-passwd=    -nv  -o log http://sec-crack.cs.rmit.edu./SEC/2/");\n\t=time(NULL);\t\n\tfor(i=0;i<52;i++)\t\n\t{\n\t\tfor(j=0;j<52;j++)\n\t\t{\n\t\t\tfor(k=0;k<52;k++)\n\t\t\t{\n\t\t\tprintf("%c %c %c\\n",arr[i],arr[j],arr[k]);\n\t\t\t\n\t\t\tadd[40]=arr[i];\n\t\t\tadd[41]=arr[j];\n\t\t\tadd[42]=arr[k];\n\t\t\tsystem(add);\n\t\t\tcount++;\n\t\t\tlog=fopen("log","r");\n\t\t\tif(log!=(FILE*)NULL)\n\t\t\tfgets(s,100,log);\n\t\t\tprintf("%s",s);\t\t\n\t\t\t\tif(strcmp(s,"Authorization failed.\\n")!=0)\n\t\t\t\t{\n\t\t\t\t\tfinish=time(NULL);\n\t\t\t\t\tttime=difftime(,finish);\n\t\t\t\t\tprintf("\\nThe password is %c%c%c \\nThe time:%f\\n The  of attempts %d",arr[i],arr[j],arr[k],ttime,count);\n\t\t\t\t\tflage=1;\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t\n\t\t\t\tfclose(log);\n\t\t\t}\n\t\t}\n\t}\n\tif(flage==0)\t\n\t{\n\t\tfor(i=0;i<52;i++)\n\t\t{\n\t\tadd[40]=arr[i];\n\t\tsystem(add);\n\t\t\tcount++;\n\t\t\tlog=fopen("log","r");\n\t\t\tif(log!=(FILE*)NULL)\n\t\t\tfgets(s,100,log);\n\t\t\tprintf("%s",s);\n\t\t\t\tif(strcmp(s,"Authorization failed.\\n")!=0)\n\t\t\t\t{\n\t\t\t\t\tfinish=time(NULL);\n\t\t\t\t\tttime=difftime(,finish);\n\t\t\t\t\tprintf("\\nThe password is %c%c%c \\nThe time:%f\\n The  of attempts %d",arr[i],ttime,count);\n\t\t\t\t\tflage=1;\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t\n\t\t\t\tfclose(log);\n\t\t}\n\t}\n\tif(flage==0)\t  \n\t{\n\t\tfor(i=0;i<52;i++)\n\t\t{\n\t\t\tfor(j=0;j<52;j++)\n\t\t\t{\n\t\t\tadd[40]=arr[i];\n\t\t\tadd[41]=arr[j];\n\t\t\tsystem(add);\n\t\t\tcount++;\n\t\t\tlog=fopen("log","r");\n\t\t\tif(log!=(FILE*)NULL)\n\t\t\tfgets(s,100,log);\n\t\t\tprintf("%s",s);\n\t\t\t\tif(strcmp(s,"Authorization failed.\\n")!=0)\n\t\t\t\t{\n\t\t\t\t\tfinish=time(NULL);\n\t\t\t\t\tttime=difftime(,finish);\n\t\t\t\t\tprintf("\\nThe password is %c%c%c \\nThe time:%f\\n The  of attempts %d",arr[i],arr[j],ttime,count);\n\t\t\t\t\tflage=1;\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t\n\t\t\t\tfclose(log);\n\t\t\t}\n\t\t}\n\t}\n\t\n}\n',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.9511, 0.9570],
#         [0.9511, 1.0000, 0.9799],
#         [0.9570, 0.9799, 1.0000]])

Training Details

Training Dataset

Unnamed Dataset

Size: 3,081 training samples
Columns: sentence_0, sentence_1, and label
Approximate statistics based on the first 1000 samples:
sentence_0 sentence_1 label
type string string int
details
min: 194 tokens
mean: 471.45 tokens
max: 512 tokens

min: 194 tokens
mean: 460.74 tokens
max: 512 tokens

0: ~99.10%
1: ~0.90%

	sentence_0	sentence_1	label
type	string	string	int
details	min: 194 tokens mean: 471.45 tokens max: 512 tokens	min: 194 tokens mean: 460.74 tokens max: 512 tokens	0: ~99.10% 1: ~0.90%

Samples:

sentence_0	sentence_1	label
#include #include #include #include #define MAX_SIZE 255 int genchkpwd(char chararray,char passwd) { int i,j,k,success; char str1[MAX_SIZE],str2[MAX_SIZE],tempstr[MAX_SIZE]; strcpy(str1,"wget --http-user= --http-passwd="); strcpy(str2," http://sec-crack.cs.rmit.edu./SEC/2/"); strcpy(tempstr,""); for(i=0;i<52;i++) { passwd[0]= chararray[i]; strcat(tempstr,str1); strcat(tempstr,passwd); strcat(tempstr,str2); printf("SENDING REQUEST AS %s\n",tempstr); success=system (tempstr); if (success==0) return 1; else strcpy(tempstr,""); strcpy(passwd,""); } for(i=0;i<52;i++) { passwd[0]= chararray[i]; for(j=0;j<52;j++) { passwd[1]=chararray[j]; strcat(tempstr,str1); strcat(tempstr,passwd); strcat(tempstr,str2); printf("SENDING REQUEST AS %s\n",tempstr); success=syste...	#include #include #include #include #include #define OneBillion 1e9 int () { int startTime, stopTime, final; int i,j,k; int pass,count=0; char arr[52] ={'A','a','B','b','C','c','D','d','E','e','F','f','G','g','H','h','I','i','J','j','K','k','L','l','M','m','N','n','O','o','P','p','Q','q','R','r','S','s','T','t','U','u','V','v','W','w','X','x','Y','y','Z','z'}; char [4]; char url1[100]; char url2[100]; startTime = time(); for (i=0;i<=52;i++) { for (j=0;j<=52;j++) { for(k=0;k<=52;k++) { count++; [0] = arr[i]; [1] = arr[j]; [2] = arr[k]; [3] = '\0'; printf("Checking for the word :%s\n",); strcpy(url1 ,"wget --http-user= --http-passwd="); strcpy(url2 , " -nv -o output http://sec-crack.cs.rmit.edu./SEC/2/ "); strcat(url1,); strcat(url1,url2); pass = system(url1); if (pass == 0) { ...	`0`
#include #include #include #include #include () { int i,m,k,count=0; FILE* diction; FILE* log; char s[30]; char pic[30]; char add[1000]; char end[100]; time_t ,finish; double ttime; strcpy(add,"wget --http-user= --http-passwd="); strcpy( end,"-nv -o logd http://sec-crack.cs.rmit.edu./SEC/2/"); diction=fopen("/usr/share/lib/dict/words","r"); =time(NULL); while(fgets(s,100,diction)!=NULL) { printf("%s\n",s); for(m=40,k=0;k<(strlen(s)-1);k++,m++) { add[m]=s[k]; } add[m++]=' '; for(i=0;i<50;i++,m++) { add[m]=end[i]; } add[m]='\0'; system(add); count++; log=fopen("logd","r"); fgets(pic,100,log); printf("%s",pic); if(strcmp(pic,"Authorization failed.\n")!=0) { finish=time(NULL); ttime=difftime(,finish); printf( "\n The time_var take:%f/n The of passwords tried is %d\n",ttime,count); break; } fclose(log); } }	#include #include #include #include #include #include #include char* joinMe(char* t, char* t2) { char* result; int length = 0; int j = 0; int counter = 0; length = strlen(t) + strlen(t2) + 1; result = malloc(sizeof(char) * length); for(j = 0; j { result[j] = t[j]; } for(j = strlen(t); j { result[j] = t2[counter]; counter++; } result[length-1] = '\0'; return result; } void check(char smallcmd) { int pid = 0; int status; if( (pid = fork()) == 0) { execvp(smallcmd[0],smallcmd); } else { while(wait(&status) != pid); } } int (void) { int i = 0, j = 0, k = 0; char smallcmd; char* [] = {"a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w", "x","y","z","A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T", "U","V","W","X","Y","Z"}; int count ...	`0`
# include # include # include # include # include int () { char s[30]; char c[100]; char usr[50]; char url[100]; char charcopy[200]; int starting,ending; int totaltime; FILE* fp; FILE* f; int i,j,k; fp = fopen("/usr/share/lib/dict/words","r"); strcpy(charcopy, "wget --http-user= --http-passwd="); strcpy(url, "-nv -o logfile1 http://sec-crack.cs.rmit.edu./SEC/2/"); starting=time(); while(!feof(fp)) { j=40; fgets(c,30,fp); for(i=0;i { charcopy[j]=c[i]; j++; } charcopy[j-1] = ' '; for(i=0;i { charcopy[j]=url[i]; j++; } charcopy[j] = '\0'; printf("%s\n",c); system(charcopy); f = fopen("logfile1","r"); if(f != (FILE*) NULL) { fgets(s,30,f); if(strcmp(s,"Authorization failed.\n")!=0) { ending=time(); totaltime=ending-starti...	#include #include #include #include #define MINSIZE 26 #define MAXSIZE 52 #define MAX_SIZE 255 int CrackPasswd(char passwd) { int flag; char string1[MAX_SIZE],string2[MAX_SIZE],[MAX_SIZE]; strcpy(string1,"wget http://sec-crack.cs.rmit.edu./SEC/2/"); strcpy(string2," --http-user= --http-passwd='"); strcpy(,""); strcat(, string1); strcat(, string2); strcat(, passwd); strcat(, "'"); printf("Sending Request as %s\n",); flag = system(); if (flag == 0) { printf("\nPassword is %s\n",passwd); return 1; } strcpy(,""); return 0; } int BruteForce(char CharArray) { int i, j, k; char passwd[MAX_SIZE]; for (i=0;i passwd[i] = '\0'; for(i=0;i { passwd[0] = CharArray[i]; if(CrackPasswd(passwd) == 1) return 1; } for(i=0;i { passwd[0] = CharArray[i]; ...	`0`

Loss: BatchAllTripletLoss

Training Hyperparameters

Non-Default Hyperparameters

per_device_train_batch_size: 16
per_device_eval_batch_size: 16
num_train_epochs: 1
fp16: True
multi_dataset_batch_sampler: round_robin

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: no
prediction_loss_only: True
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 5e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1
num_train_epochs: 1
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.0
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: False
fp16: True
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: False
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: None
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
include_for_metrics: []
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
eval_use_gather_object: False
average_tokens_across_devices: False
prompts: None
batch_sampler: batch_sampler
multi_dataset_batch_sampler: round_robin
router_mapping: {}
learning_rate_mapping: {}

Framework Versions

Python: 3.11.13
Sentence Transformers: 5.0.0
Transformers: 4.52.4
PyTorch: 2.6.0+cu124
Accelerate: 1.8.1
Datasets: 3.6.0
Tokenizers: 0.21.2

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

BatchAllTripletLoss

@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}