buelfhood / SOCO-Java-CodeBERTa-ST-1

huggingface.co
Total runs: 110
24-hour runs: 2
7-day runs: -26
30-day runs: -1
Model's Last Updated: June 11 2025
sentence-similarity

Introduction of SOCO-Java-CodeBERTa-ST-1

Model Details of SOCO-Java-CodeBERTa-ST-1

SentenceTransformer based on huggingface/CodeBERTa-small-v1

This is a sentence-transformers model finetuned from huggingface/CodeBERTa-small-v1 . 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
Model Sources
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/SOCO-Java-CodeBERTa-ST-1")
# Run inference
sentences = [
    '\npackage java.httputils;\n\nimport java.io.IOException;\nimport java.net.HttpURLConnection;\nimport java.net.MalformedURLException;\nimport java.net.URL;\nimport java.sql.Timestamp;\n\n\npublic class BasicAuthHttpRequest extends HttpRequestClient\n{\n    String userName;\n    String password;\n    \n    protected BasicAuthHttpRequest(String url, String userName, String password)\n        throws MalformedURLException, IOException\n    {\n        setPassword(password);\n        setUserName(userName);\n        setServerURL(new URL(url));\n        \n        setStart(new Timestamp(System.currentTimeMillis()));\n\n        String userPassword = userName + ":" + password;\n\n        \n        String encoding = new url.misc.BASE64Encoder().encode (userPassword.getBytes());\n\n       \n\n       setHttpConnection(\n        (HttpURLConnection)this.getServerURL().openConnection());\n\n        \n        getHttpConnection().setRequestProperty ("Authorization", " " + encoding);\n        doRequest();\n    }\n\n    \n    protected BasicAuthHttpRequest(String url)\n        throws MalformedURLException, IOException\n    {\n        super(url);\n    }\n\n    \n    public BasicAuthHttpRequest()\n    {\n        super();\n    }\n\n\n    \n    public String getPassword()\n    {\n        return password;\n    }\n\n    \n    public String getUserName()\n    {\n        return userName;\n    }\n\n    \n    public void setPassword(String string)\n    {\n        password = string;\n    }\n\n    \n    public void setUserName(String string)\n    {\n        userName = string;\n    }\n\n    public static void main (String[] args)\n    {\n        BasicAuthHttpRequest client = null;\n        try\n        {\n            client = new BasicAuthHttpRequest(args[0], args[1], args[2]);\n        }\n        catch (MalformedURLException e)\n        {\n            e.printStackTrace();\n        }\n        catch (IOException e)\n        {\n            e.printStackTrace();\n        }\n        finally\n        {\n            if (client != null && client.getCode() != HttpURLConnection.HTTP_UNAUTHORIZED)\n            {\n                System.out.println(\n                    "Request response : \\n" + client.getCode());\n\n\n                System.out.println(\n                    "Request processing time (milliseconds): " +\n                    (client.getEnd().getTime() - client.getStart().getTime()));\n\n                System.out.println(\n                    "Request content: \\n" + client.getContent());\n            }\n            else\n            {\n                System.out.println(\n                    "Request response : \\n" + client.getCode());\n\n\n            }\n        }\n    }\n}\n',
    'import java.io.*;\nimport java.net.*;\nimport java.security.*;\nimport java.math.*;\nimport java.*;\nimport java.util.*;\n\n\npublic class WatchDog\n{\n    public static FileWriter out = null, output = null;\n\n    public static void main (String args[]) throws Exception {\n\tSocket socket = null;\n\tDataOutputStream  = null;\n\tBufferedReader bf = null, fr = null;\n\tString retVal = null, StatusCode = "HTTP/1.1 200 OK";\n    int dirty = 0, count = 0;\n\n         stime = System.currentTimeMillis();\n        System.out.println("Detecting the changes...");\n\n        try {\n\n\t        \n            URL yahoo = new URL("http://www.cs.rmit.edu./students/");\n            URLConnection yc = yahoo.openConnection();\n\n            \n            BufferedReader in = new BufferedReader(\n                                    new InputStreamReader(\n                                    yc.getInputStream()));\n\n            String inputLine;\n            try {\n                out = new FileWriter("newstudent");\n                while ((inputLine = in.readLine()) != null){\n                        out.write(inputLine + "\\n");\n                }\n            } catch (IOException ex) {\n                ex.printStackTrace();\n            }\n            in.print();\n            out.print();\n\n            dirty = diff();\n            if (dirty == 1){\n               sendMail();\n               System.out.println("Changes detected and email sent!");\n            }\n\n            if (diffimages() == 1){\n               sendMail();\n               System.out.println("Images modification detected and email sent!");\n            }\n\n            updatePage();\n            System.out.println("** End of WatchDog checking **");\n\n            } catch (Exception ex) {\n              ex.printStackTrace();\n            }\n    }\n\n    public static int diff()\n    {\n       int update = 0;\n\n       try{\n           Process process = Runtime.getRuntime().exec("diff -b RMITCSStudent newstudent");\n           BufferedReader pr = new BufferedReader(\n                                   new InputStreamReader(\n                                   process.getInputStream()));\n\n           output = new FileWriter("output");\n           String inputLine;\n           while ((inputLine = pr.readLine()) != null){\n                 output.write(inputLine + "\\n");\n                 update = 1;\n           }\n           output.promt();\n\n       }catch (Exception ex){\n              ex.printStackTrace();\n       }\n       return update;\n    }\n\n    public static int diffimages()\n    {\n       int update = 0;\n       String image;\n\n       try{\n           Process primages = Runtime.getRuntime().exec("./images.sh");\n           wait(1);\n           File imageFile = new File("imagesname");\n           BufferedReader fr = new BufferedReader(new FileReader(imageFile));\n\n           output = new FileWriter("output");\n           while ((image = fr.readLine()) != null) {\n                 primages = Runtime.getRuntime().exec("diff " + image + " o"+image);\n                 BufferedReader pr = new BufferedReader(\n                                       new InputStreamReader(\n                                       primages.getInputStream()));\n\n                 String inputLine;\n                 while ((inputLine = pr.readLine()) != null){\n                       output.write(inputLine + "\\n");\n                       update = 1;\n                 }\n           }\n           output.print();\n           fr.close();\n\n       }catch (Exception ex){\n              ex.printStackTrace();\n       }\n       return update;\n    }\n\n    public static void sendMail()\n    {\n       try{\n           Process mailprocess = Runtime.getRuntime().exec("./email.sh");\n       }catch (Exception ex){\n           ex.printStackTrace();\n       }\n    }\n\n    public static void updatePage()\n    {\n       String image;\n\n       try{\n           Process updateprocess = Runtime.getRuntime().exec("cp newstudent RMITCSStudent");\n           Process deleteprocess = Runtime.getRuntime().exec("rm newstudent");\n\n           File inputFile = new File("imagesname");\n           BufferedReader fr = new BufferedReader(new FileReader(inputFile));\n           while ((image = fr.readLine()) != null) {\n                 updateprocess = Runtime.getRuntime().exec("cp " + image + " o" + image);\n                 deleteprocess = Runtime.getRuntime().exec("rm " + image);\n           }\n           fr.close();\n       }catch (Exception ex){\n           ex.printStackTrace();\n       }\n    }\n\n    public static void wait(int time){\n\t   int timer, times;\n\t   timer = System.currentTimeMillis();\n\t   times = (time * 1000) + timer;\n\n\t   while(timer < times)\n\t\t\ttimer = System.currentTimeMillis();\n\t}\n}',
    'import java.net.*;\nimport java.io.*;\n\n\npublic class EmailClient\n{\n\tprivate String sender, recipient, hostName;\n\n\tpublic EmailClient(String nSender, String nRecipient, String nHost)\n\t{\n\t\tsender = nSender;\n\t\trecipient = nRecipient;\n\t\thostName = nHost;\n\t}\n\n\tpublic void sendMail(String subject, String message)\n\t{\n\t\ttry\n\t\t{\n\t\t\tSocket s1=null;\n\t\t\tInputStream\tis = null;\n\t\t\tOutputStream os = null;\n\n\t\t\tDataOutputStream  = null;\n\n\t\t\ts1 = new Socket(hostName,25);\n\t\t\tis = s1.getInputStream();\n\t\t\tos = s1.getOutputStream();\n\n\t\t\tbd = new DataOutputStream(os);\n\n\t\t\tBufferedReader response = new BufferedReader(new InputStreamReader(is));\n\n\t\t\tbd.writeBytes("HELO "+ InetAddress.getLocalHost().getHostName() + "\\r\\n");\n\n\t\t\twaitForSuccessResponse(response);\n\n\t\t\tbd.writeBytes("MAIL FROM:"+sender+"\\n");\n\n\t\t\twaitForSuccessResponse(response);\n\n\t\t\tbd.writeBytes("RCPT :"+recipient+"\\n");\n\n\t\t\twaitForSuccessResponse(response);\n\n\t\t\tbd.writeBytes("data"+"\\n");\n\n\t\t\tbd.writeBytes("Subject:"+subject+"\\n");\n\n\t\t\tbd.writeBytes(message+"\\n.\\n");\n\n\t\t\twaitForSuccessResponse(response);\n\t\t}\n\n\t\tcatch (UnknownHostException badUrl)\n\t\t{\n\t\t\tSystem.out.println("Host unknown.");\n\t\t}\n\n\t\tcatch (EOFException eof)\n\t\t{\n\t\t\tSystem.out.println("<EOF>");\n\t\t}\n\t\tcatch (Exception e)\n\t\t{\n\t\t\tSystem.out.println("got exception: "+e);\n\t\t}\n\t}\n\n\tprivate static void\twaitForSuccessResponse(BufferedReader response) throws IOException\n\t{\n\t\tString rsp;\n\t\tboolean r250 = false;\n\n\t\twhile( ! r250 )\n\t\t{\n\t\t\trsp = response.readLine().trim();\n\n\t\t\tif(rsp.startsWith("250"))\n\t\t\t\tr250 = true;\n\t\t}\n\n\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
Unnamed Dataset
  • Size: 33,411 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: 51 tokens
    • mean: 444.12 tokens
    • max: 512 tokens
    • min: 54 tokens
    • mean: 462.06 tokens
    • max: 512 tokens
    • 0: ~99.80%
    • 1: ~0.20%
  • Samples:
    sentence_0 sentence_1 label



    import java.net. ;
    import java.io.
    ;
    import java.Runtime;

    public class WatchDog{
    public WatchDog(){}


    public void copyTo(){

    }

    public static void main(String[] args) throws Exception {
    WatchDog wd= new WatchDog();
    SendEMail t = new SendEMail();
    PrintWriter pw=null;
    URL url = new URL(" http://www.cs.rmit.edu./students ");
    URLConnection yc = url.openConnection();
    System.out.println("Connection opened...");
    BufferedReader in = new BufferedReader(new InputStreamReader(yc.getInputStream()));
    String inputLine;
    try{
    pw=new PrintWriter(new FileOutputStream("newHtml"));
    while ((inputLine = in.readLine()) != null){

    pw.println(inputLine);
    }
    pw.save();
    }catch(IOException e){
    System.out.println("Error saving the file");
    }


    Process p = Runtime.getRuntime().exec("diff -b newHtml oldHtml");
    ...




    import java.io. ;
    import java.net.
    ;
    import java. ;
    import java.util.
    ;

    public class DictionaryAttack
    {
    public static void main ( String args[])
    {

    String function,pass,temp1;
    int count =0;

    try{

    FileReader fr = new FileReader("words.txt");
    BufferedReader bfread = new BufferedReader(fr);

    Runtime rtime = Runtime.getRuntime();
    Process prs = null;


    while(( bf = bfread.readLine()) != null)
    {


    if( f.length() < 4 )
    {
    System.out.println(+ " The Attack Number =====>" + count++ );
    pass = f;

    function ="wget --http-user= --http-passwd="+pass+" http://sec-crack.cs.rmit.edu./SEC/2/ ";
    prs = rtime.exec(function);

    InputStreamReader stre = new InputStreamReader(prs.getErrorStream());
    BufferedReader bread = new BufferedReader(stre);
    while( (temp1 = bread.readLine())!= null)
    {
    System.out.println(temp1);
    if(temp1.equals("HTTP request sent, awaiting resp...
    0




    import java.net. ;
    import java.io.
    ;
    import java.util. ;

    public class WatchDog
    {

    public WatchDog()
    {
    }

    public static void main(String[] args)
    {
    try
    {
    if( args.length != 2 )
    {
    System.out.println("USAGE: java WatchDog ");
    System.exit(0);
    }

    Runtime.getRuntime().exec("rm LastWatch.html");
    Runtime.getRuntime().exec("rm WatchDog.ini");

    Thread.sleep(1000);

    while (true)
    {
    WatchDog myWatchDog = new WatchDog();
    myWatchDog.readHTML(args[0], args[1]);

    Runtime.getRuntime().exec("rm Report.txt");
    Runtime.getRuntime().exec("rm diffReport.txt");
    Runtime.getRuntime().exec("rm NewWatch.txt");

    System.out.println(" check after 2 ... press Ctrl-Z suspend WatchDog...");

    Thread.sleep(2
    60*1000);


    }
    ...


    import java.net. ;
    import java.io.
    ;


    class MyAuthenticator extends Authenticator {

    String password;

    public MyAuthenticator(String pwdin) {
    password = pwdin;
    }

    protected PasswordAuthentication getPasswordAuthentication(){
    String pwd = password;
    return new PasswordAuthentication("",pwd.toCharArray());
    }
    }
    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();
    }
    }




    public class HoldSharedData
    {
    private int numOfConnections = 0;
    private int startTime;
    private int totalTime = 0;
    private String[] password;
    private int pwdCount;

    public HoldSharedData( int time, String[] pwd, int count )
    {
    startTime = time;

    password = pwd;
    pwdCount = count;
    }

    public int getPwdCount()
    {
    return pwdCount;
    }

    public void setNumOfConnections( )
    {
    numOfConnections ++;
    }

    public int getNumOfConnections()
    {
    return numOfConnections;
    }

    public int getStartTime()
    {
    return startTime;
    }

    public void setTotalTime( int newTotalTime )
    {
    totalTime = newTotalTime;
    }

    public int getTotalTime()
    {
    return totalTime;
    }

    public String getPasswordAt( int index )
    {
    return password[index];
    }
    }
    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
Training Logs
Epoch Step Training Loss
0.2393 500 0.2031
0.4787 1000 0.1761
0.7180 1500 0.1914
0.9574 2000 0.2044
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
@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}
}

Runs of buelfhood SOCO-Java-CodeBERTa-ST-1 on huggingface.co

110
Total runs
2
24-hour runs
0
3-day runs
-26
7-day runs
-1
30-day runs

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