cs-job-resume-model / README.md

hetbhagatji09

Add new SentenceTransformer model

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metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - dense
  - generated_from_trainer
  - dataset_size:480
  - loss:MultipleNegativesRankingLoss
base_model: sentence-transformers/all-mpnet-base-v2
widget:
  - source_sentence: >-
      Backend Developer required. Looking for expertise in Python, Django, REST
      APIs, Databases, Caching.Python;Django;REST APIs;Databases;Caching
    sentences:
      - >-
        Summary: 2+ years experience. Skills: React, PostgreSQL, Docker,
        MongoDB, REST, Unit Testing. Projects: Worked on a project that
        implemented React and PostgreSQL to deliver production-ready features,
        collaborated in Agile teams. Experience: 2 years developing systems
        using React, PostgreSQL, Docker, MongoDB.React;PostgreSQL;Docker;MongoDB
      - >-
        Summary: 6+ years experience. Skills: Android SDK, Swift, iOS SDK,
        Kotlin, CI/CD, APIs. Projects: Worked on a project that implemented
        Android SDK and Swift to deliver production-ready features, collaborated
        in Agile teams. Experience: 6 years developing systems using Android
        SDK, Swift, iOS SDK, Kotlin.Android SDK;Swift;iOS SDK;Kotlin
      - >-
        Summary: Experience in Caching, Python, Django and related
        tools.Caching;Python;Django
  - source_sentence: >-
      Backend Developer required. Looking for expertise in Python, Django, REST
      APIs, Databases, Caching.Python;Django;REST APIs;Databases;Caching
    sentences:
      - >-
        Summary: Experience in Excel, ETL, PowerBI and related
        tools.Excel;ETL;PowerBI
      - >-
        Summary: 4+ years experience. Skills: Jenkins, Terraform, Grafana,
        Prometheus, TDD, Git. Projects: Worked on a project that implemented
        Jenkins and Terraform to deliver production-ready features, collaborated
        in Agile teams. Experience: 4 years developing systems using Jenkins,
        Terraform, Grafana, Prometheus.Jenkins;Terraform;Grafana;Prometheus
      - >-
        Summary: Experience in Python, REST APIs, Databases and related
        tools.Python;REST APIs;Databases
  - source_sentence: >-
      Mobile Engineer required. We are looking for an engineer with 1+ years of
      experience. Responsibilities include building and maintaining systems
      using REST APIs, Objective-C, Android SDK, iOS SDK. Familiarity with
      Linux, APIs is a plus. Experience with scalable systems and good
      engineering practices required.REST APIs;Objective-C;Android SDK;iOS SDK
    sentences:
      - >-
        Summary: 5+ years experience. Skills: Spark, ETL, TensorFlow,
        Kubernetes, CI/CD, Linux. Projects: Worked on a project that implemented
        Spark and ETL to deliver production-ready features, collaborated in
        Agile teams. Experience: 5 years developing systems using Spark, ETL,
        TensorFlow, Kubernetes.Spark;ETL;TensorFlow;Kubernetes
      - >-
        Summary: 1+ years experience. Skills: TensorFlow, Spark, Kubernetes,
        PyTorch, TDD, Unit Testing. Projects: Worked on a project that
        implemented TensorFlow and Spark to deliver production-ready features,
        collaborated in Agile teams. Experience: 1 years developing systems
        using TensorFlow, Spark, Kubernetes,
        PyTorch.TensorFlow;Spark;Kubernetes;PyTorch
      - >-
        Summary: 2+ years experience. Skills: Python, Django, CI/CD, Node.js,
        Agile, Linux. Projects: Worked on a project that implemented Python and
        Django to deliver production-ready features, collaborated in Agile
        teams. Experience: 2 years developing systems using Python, Django,
        CI/CD, Node.js.Python;Django;CI/CD;Node.js
  - source_sentence: >-
      DevOps Engineer required. We are looking for an engineer with 5+ years of
      experience. Responsibilities include building and maintaining systems
      using Grafana, Docker, Prometheus, Terraform. Familiarity with APIs, CI/CD
      is a plus. Experience with scalable systems and good engineering practices
      required.Grafana;Docker;Prometheus;Terraform
    sentences:
      - >-
        Summary: Experience in SQL, PostgreSQL, Optimization and related
        tools.SQL;PostgreSQL;Optimization
      - >-
        Summary: 5+ years experience. Skills: Java, React Native, Objective-C,
        Flutter, APIs, Unit Testing. Projects: Worked on a project that
        implemented Java and React Native to deliver production-ready features,
        collaborated in Agile teams. Experience: 5 years developing systems
        using Java, React Native, Objective-C, Flutter.Java;React
        Native;Objective-C;Flutter
      - >-
        Summary: 7+ years experience. Skills: CI/CD, Grafana, Ansible, GCP,
        APIs, REST. Projects: Worked on a project that implemented CI/CD and
        Grafana to deliver production-ready features, collaborated in Agile
        teams. Experience: 7 years developing systems using CI/CD, Grafana,
        Ansible, GCP.CI/CD;Grafana;Ansible;GCP
  - source_sentence: >-
      Full Stack Engineer required. We are looking for an engineer with 1+ years
      of experience. Responsibilities include building and maintaining systems
      using Python, Express, React, JavaScript. Familiarity with Unit Testing,
      Agile is a plus. Experience with scalable systems and good engineering
      practices required.Python;Express;React;JavaScript
    sentences:
      - >-
        Summary: 6+ years experience. Skills: SASS, TypeScript, Tailwind,
        JavaScript, REST, APIs. Projects: Worked on a project that implemented
        SASS and TypeScript to deliver production-ready features, collaborated
        in Agile teams. Experience: 6 years developing systems using SASS,
        TypeScript, Tailwind, JavaScript.SASS;TypeScript;Tailwind;JavaScript
      - >-
        Summary: 5+ years experience. Skills: Express, CI/CD, React, JavaScript,
        Git, APIs. Projects: Worked on a project that implemented Express and
        CI/CD to deliver production-ready features, collaborated in Agile teams.
        Experience: 5 years developing systems using Express, CI/CD, React,
        JavaScript.Express;CI/CD;React;JavaScript
      - >-
        Summary: Experience in Android Studio, Kotlin, Java and related
        tools.Android Studio;Kotlin;Java
datasets:
  - hetbhagatji09/job-resume-embedding-finetuning
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - cosine_accuracy
model-index:
  - name: SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
    results:
      - task:
          type: triplet
          name: Triplet
        dataset:
          name: ai job validation
          type: ai-job-validation
        metrics:
          - type: cosine_accuracy
            value: 0.75
            name: Cosine Accuracy
      - task:
          type: triplet
          name: Triplet
        dataset:
          name: ai job test
          type: ai-job-test
        metrics:
          - type: cosine_accuracy
            value: 0.7333333492279053
            name: Cosine Accuracy

SentenceTransformer based on sentence-transformers/all-mpnet-base-v2

This is a sentence-transformers model finetuned from sentence-transformers/all-mpnet-base-v2 on the job-resume-embedding-finetuning 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: sentence-transformers/all-mpnet-base-v2
Maximum Sequence Length: 384 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Cosine Similarity
Training Dataset:
- job-resume-embedding-finetuning

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': 384, 'do_lower_case': False, 'architecture': 'MPNetModel'})
  (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})
  (2): Normalize()
)

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("hetbhagatji09/cs-job-resume-model")
# Run inference
queries = [
    "Full Stack Engineer required. We are looking for an engineer with 1+ years of experience. Responsibilities include building and maintaining systems using Python, Express, React, JavaScript. Familiarity with Unit Testing, Agile is a plus. Experience with scalable systems and good engineering practices required.Python;Express;React;JavaScript",
]
documents = [
    'Summary: 5+ years experience. Skills: Express, CI/CD, React, JavaScript, Git, APIs. Projects: Worked on a project that implemented Express and CI/CD to deliver production-ready features, collaborated in Agile teams. Experience: 5 years developing systems using Express, CI/CD, React, JavaScript.Express;CI/CD;React;JavaScript',
    'Summary: Experience in Android Studio, Kotlin, Java and related tools.Android Studio;Kotlin;Java',
    'Summary: 6+ years experience. Skills: SASS, TypeScript, Tailwind, JavaScript, REST, APIs. Projects: Worked on a project that implemented SASS and TypeScript to deliver production-ready features, collaborated in Agile teams. Experience: 6 years developing systems using SASS, TypeScript, Tailwind, JavaScript.SASS;TypeScript;Tailwind;JavaScript',
]
query_embeddings = model.encode_query(queries)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings.shape)
# [1, 768] [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(query_embeddings, document_embeddings)
print(similarities)
# tensor([[0.7931, 0.3914, 0.7911]])

Evaluation

Metrics

Triplet

Datasets: ai-job-validation and ai-job-test
Evaluated with TripletEvaluator

Metric	ai-job-validation	ai-job-test
cosine_accuracy	0.75	0.7333

Training Details

Training Dataset

job-resume-embedding-finetuning

Dataset: job-resume-embedding-finetuning at d15c797
Size: 480 training samples
Columns: query, job_description_pos, and job_description_neg

Approximate statistics based on the first 480 samples:

	query	job_description_pos	job_description_neg
type	string	string	string
details	min: 33 tokens mean: 67.54 tokens max: 85 tokens	min: 22 tokens mean: 76.39 tokens max: 113 tokens	min: 22 tokens mean: 76.92 tokens max: 113 tokens

Samples:

query	job_description_pos	job_description_neg
`Frontend Developer required. We are looking for an engineer with 5+ years of experience. Responsibilities include building and maintaining systems using CSS, SASS, Tailwind, React. Familiarity with APIs, Unit Testing is a plus. Experience with scalable systems and good engineering practices required.CSS;SASS;Tailwind;React`	`Summary: 2+ years experience. Skills: Flutter, Kotlin, REST APIs, iOS SDK, TDD, APIs. Projects: Worked on a project that implemented Flutter and Kotlin to deliver production-ready features, collaborated in Agile teams. Experience: 2 years developing systems using Flutter, Kotlin, REST APIs, iOS SDK.Flutter;Kotlin;REST APIs;iOS SDK`	`Summary: 2+ years experience. Skills: Spark, NumPy, ETL, PyTorch, Agile, Linux. Projects: Worked on a project that implemented Spark and NumPy to deliver production-ready features, collaborated in Agile teams. Experience: 2 years developing systems using Spark, NumPy, ETL, PyTorch.Spark;NumPy;ETL;PyTorch`
`React Native Developer required. We are looking for an engineer with 4+ years of experience. Responsibilities include building and maintaining systems using Flutter, Android SDK, Objective-C, Kotlin. Familiarity with Unit Testing, REST is a plus. Experience with scalable systems and good engineering practices required.Flutter;Android SDK;Objective-C;Kotlin`	`Summary: 5+ years experience. Skills: Prometheus, Jenkins, CI/CD, Terraform, Git, CI/CD. Projects: Worked on a project that implemented Prometheus and Jenkins to deliver production-ready features, collaborated in Agile teams. Experience: 5 years developing systems using Prometheus, Jenkins, CI/CD, Terraform.Prometheus;Jenkins;CI/CD;Terraform`	`Summary: 5+ years experience. Skills: Flask, REST APIs, Python, SQL, Unit Testing, TDD. Projects: Worked on a project that implemented Flask and REST APIs to deliver production-ready features, collaborated in Agile teams. Experience: 5 years developing systems using Flask, REST APIs, Python, SQL.Flask;REST APIs;Python;SQL`
`Data Analyst required. Looking for expertise in SQL, PowerBI, Excel, Visualization, ETL.SQL;PowerBI;Excel;Visualization;ETL`	`Summary: Experience in PowerBI, Excel, Visualization and related tools.PowerBI;Excel;Visualization`	`Summary: 1+ years experience. Skills: Docker, MySQL, Django, Kubernetes, TDD, Agile. Projects: Worked on a project that implemented Docker and MySQL to deliver production-ready features, collaborated in Agile teams. Experience: 1 years developing systems using Docker, MySQL, Django, Kubernetes.Docker;MySQL;Django;Kubernetes`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "cos_sim",
    "gather_across_devices": false
}

Evaluation Dataset

job-resume-embedding-finetuning

Dataset: job-resume-embedding-finetuning at d15c797
Size: 60 evaluation samples
Columns: query, job_description_pos, and job_description_neg

Approximate statistics based on the first 60 samples:

	query	job_description_pos	job_description_neg
type	string	string	string
details	min: 33 tokens mean: 68.63 tokens max: 83 tokens	min: 22 tokens mean: 77.83 tokens max: 105 tokens	min: 22 tokens mean: 76.6 tokens max: 100 tokens

Samples:

query	job_description_pos	job_description_neg
`JavaScript Engineer required. We are looking for an engineer with 3+ years of experience. Responsibilities include building and maintaining systems using HTML, React, CSS, JavaScript. Familiarity with APIs, REST is a plus. Experience with scalable systems and good engineering practices required.HTML;React;CSS;JavaScript`	`Summary: 7+ years experience. Skills: React, Babel, HTML, Tailwind, Git, TDD. Projects: Worked on a project that implemented React and Babel to deliver production-ready features, collaborated in Agile teams. Experience: 7 years developing systems using React, Babel, HTML, Tailwind.React;Babel;HTML;Tailwind`	`Summary: 7+ years experience. Skills: Flask, Python, Django, PostgreSQL, APIs, Linux. Projects: Worked on a project that implemented Flask and Python to deliver production-ready features, collaborated in Agile teams. Experience: 7 years developing systems using Flask, Python, Django, PostgreSQL.Flask;Python;Django;PostgreSQL`
`Android Developer required. Looking for expertise in Kotlin, Java, Android Studio, XML, Jetpack.Kotlin;Java;Android Studio;XML;Jetpack`	`Summary: Experience in Jetpack, XML, Android Studio and related tools.Jetpack;XML;Android Studio`	`Summary: 3+ years experience. Skills: Node.js, Python, PostgreSQL, Docker, Git, REST. Projects: Worked on a project that implemented Node.js and Python to deliver production-ready features, collaborated in Agile teams. Experience: 3 years developing systems using Node.js, Python, PostgreSQL, Docker.Node.js;Python;PostgreSQL;Docker`
`Backend Developer required. Looking for expertise in Python, Django, REST APIs, Databases, Caching.Python;Django;REST APIs;Databases;Caching`	`Summary: Experience in Django, Caching, Databases and related tools.Django;Caching;Databases`	`Summary: 2+ years experience. Skills: Grafana, AWS, Docker, CI/CD, CI/CD, Linux. Projects: Worked on a project that implemented Grafana and AWS to deliver production-ready features, collaborated in Agile teams. Experience: 2 years developing systems using Grafana, AWS, Docker, CI/CD.Grafana;AWS;Docker;CI/CD`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "cos_sim",
    "gather_across_devices": false
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
learning_rate: 2e-05
num_train_epochs: 1
warmup_ratio: 0.1
batch_sampler: no_duplicates

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
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
bf16: False
fp16: False
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}
parallelism_config: None
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch_fused
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
project: huggingface
trackio_space_id: trackio
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
hub_revision: None
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: no
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
liger_kernel_config: None
eval_use_gather_object: False
average_tokens_across_devices: True
prompts: None
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional
router_mapping: {}
learning_rate_mapping: {}

Training Logs

Epoch	Step	ai-job-validation_cosine_accuracy	ai-job-test_cosine_accuracy
-1	-1	0.75	0.7333

Framework Versions

Python: 3.12.12
Sentence Transformers: 5.1.2
Transformers: 4.57.2
PyTorch: 2.9.0+cu126
Accelerate: 1.12.0
Datasets: 4.0.0
Tokenizers: 0.22.1

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",
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}