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---
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) <!-- at revision e8c3b32edf5434bc2275fc9bab85f82640a19130 -->
- **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)
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### 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]])
```
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</details>
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You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
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## Evaluation
### Metrics
#### Triplet
* Datasets: `ai-job-validation` and `ai-job-test`
* Evaluated with [<code>TripletEvaluator</code>](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** |
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## 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: <code>query</code>, <code>job_description_pos</code>, and <code>job_description_neg</code>
* Approximate statistics based on the first 480 samples:
| | query | job_description_pos | job_description_neg |
|:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
| type | string | string | string |
| details | <ul><li>min: 33 tokens</li><li>mean: 67.54 tokens</li><li>max: 85 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 76.39 tokens</li><li>max: 113 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 76.92 tokens</li><li>max: 113 tokens</li></ul> |
* Samples:
| query | job_description_pos | job_description_neg |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>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</code> | <code>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</code> | <code>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</code> |
| <code>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</code> | <code>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</code> | <code>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</code> |
| <code>Data Analyst required. Looking for expertise in SQL, PowerBI, Excel, Visualization, ETL.SQL;PowerBI;Excel;Visualization;ETL</code> | <code>Summary: Experience in PowerBI, Excel, Visualization and related tools.PowerBI;Excel;Visualization</code> | <code>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</code> |
* Loss: [<code>MultipleNegativesRankingLoss</code>](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: <code>query</code>, <code>job_description_pos</code>, and <code>job_description_neg</code>
* Approximate statistics based on the first 60 samples:
| | query | job_description_pos | job_description_neg |
|:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string | string |
| details | <ul><li>min: 33 tokens</li><li>mean: 68.63 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 77.83 tokens</li><li>max: 105 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 76.6 tokens</li><li>max: 100 tokens</li></ul> |
* Samples:
| query | job_description_pos | job_description_neg |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>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</code> | <code>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</code> | <code>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</code> |
| <code>Android Developer required. Looking for expertise in Kotlin, Java, Android Studio, XML, Jetpack.Kotlin;Java;Android Studio;XML;Jetpack</code> | <code>Summary: Experience in Jetpack, XML, Android Studio and related tools.Jetpack;XML;Android Studio</code> | <code>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</code> |
| <code>Backend Developer required. Looking for expertise in Python, Django, REST APIs, Databases, Caching.Python;Django;REST APIs;Databases;Caching</code> | <code>Summary: Experience in Django, Caching, Databases and related tools.Django;Caching;Databases</code> | <code>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</code> |
* Loss: [<code>MultipleNegativesRankingLoss</code>](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
<details><summary>Click to expand</summary>
- `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`: {}
</details>
### 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}
}
```
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