--- 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](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the [job-resume-embedding-finetuning](https://huggingface.co/datasets/hetbhagatji09/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](https://huggingface.co/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](https://huggingface.co/datasets/hetbhagatji09/job-resume-embedding-finetuning) ### Model Sources - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) ### 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: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python 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](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.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](https://huggingface.co/datasets/hetbhagatji09/job-resume-embedding-finetuning) at [d15c797](https://huggingface.co/datasets/hetbhagatji09/job-resume-embedding-finetuning/tree/d15c79748f157c712ae5e8c496db091adc93a6c1) * 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 | | | | * 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](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters: ```json { "scale": 20.0, "similarity_fct": "cos_sim", "gather_across_devices": false } ``` ### Evaluation Dataset #### job-resume-embedding-finetuning * Dataset: [job-resume-embedding-finetuning](https://huggingface.co/datasets/hetbhagatji09/job-resume-embedding-finetuning) at [d15c797](https://huggingface.co/datasets/hetbhagatji09/job-resume-embedding-finetuning/tree/d15c79748f157c712ae5e8c496db091adc93a6c1) * 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 | | | | * 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](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters: ```json { "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 ```bibtex @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 ```bibtex @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} } ```