--- tags: - sentence-transformers - sentence-similarity - feature-extraction - dense - generated_from_trainer - dataset_size:333 - loss:CosineSimilarityLoss base_model: sentence-transformers/all-MiniLM-L6-v2 widget: - source_sentence: brain scan sentences: - 'Full WordPress Site Health Audit. Check plugins — installed, active, and update status command Verify SEO configuration command Test page speed with Lighthouse command Security check — WordFence scan and login protection check Test REST API connectivity and credentials command Check Google Search Console for crawl errors and ranking prompt. Tags: wordpress, audit, seo, security, performance, plugins, health' - 'Bulk Article Creation for a Site. Research topics and identify content gaps command Generate content outlines and briefs command Write content using ZimmWriter or scripts prompt Generate featured images for all articles command Publish articles and set featured images command. Tags: content, articles, bulk, wordpress, seo, publishing, zimmwriter' - 'Run EMPIRE-BRAIN Scan and Intelligence Cycle. Run full empire brain scan command Generate intelligence briefing command Check brain stats and performance metrics command Run evolution cycle command Verify Sentinel service monitoring status command. Tags: empire, brain, scan, intelligence, monitoring, evolution, briefing' - source_sentence: check vps sentences: - 'Cross-Site Internal Linking Strategy. Identify cluster and linking opportunities check Find matching content between cluster sites command Generate and inject cross-links command Verify and monitor link health command. Tags: seo, internal-links, cross-site, clusters, link-whisper, revenue' - 'Full WordPress Site Health Audit. Check plugins — installed, active, and update status command Verify SEO configuration command Test page speed with Lighthouse command Security check — WordFence scan and login protection check Test REST API connectivity and credentials command Check Google Search Console for crawl errors and ranking prompt. Tags: wordpress, audit, seo, security, performance, plugins, health' - 'Full WordPress Site Health Audit. Check plugins — installed, active, and update status command Verify SEO configuration command Test page speed with Lighthouse command Security check — WordFence scan and login protection check Test REST API connectivity and credentials command Check Google Search Console for crawl errors and ranking prompt. Tags: wordpress, audit, seo, security, performance, plugins, health' - source_sentence: performance optim sentences: - 'Run EMPIRE-BRAIN Scan and Intelligence Cycle. Run full empire brain scan command Generate intelligence briefing command Check brain stats and performance metrics command Run evolution cycle command Verify Sentinel service monitoring status command. Tags: empire, brain, scan, intelligence, monitoring, evolution, briefing' - 'Site Speed & Core Web Vitals Optimization. Run Lighthouse audit command Configure LiteSpeed Cache (all sites use it) command Image optimization check Font and render-blocking resource optimization check Verify improvements and monitor command. Tags: seo, speed, performance, core-web-vitals, litespeed, images, caching' - 'WordPress Plugin Deployment to Sites. Check if plugin is available on WorldPressIT check Install via WordPress REST API or WP-CLI command Configure plugin settings prompt Verify no conflicts with existing plugins check Deploy fleet-wide if applicable prompt. Tags: wordpress, plugin, deploy, fleet' - source_sentence: make pinterest pin sentences: - 'Generate Article Featured Images. Run article_images_pipeline.py with correct arguments command Verify the featured image was set check. Tags: content, images, wordpress, featured-image' - 'Social Media Post Generation & Scheduling. Generate platform-specific images command Write platform-specific copy prompt Schedule or post via automation command. Tags: content, social, pinterest, instagram, facebook, twitter, scheduling' - 'Bootstrap a New Empire Project. Create project directory and initialize git command Create PROJECT_DNA.md command Create CLAUDE.md with project-specific config prompt Set up Python environment command Create initial git commit and push to GitHub command Register project in EMPIRE-BRAIN command. Tags: empire, project, bootstrap, setup, new' - source_sentence: batch articles sentences: - 'Bulk Article Creation for a Site. Research topics and identify content gaps command Generate content outlines and briefs command Write content using ZimmWriter or scripts prompt Generate featured images for all articles command Publish articles and set featured images command. Tags: content, articles, bulk, wordpress, seo, publishing, zimmwriter' - 'Site Speed & Core Web Vitals Optimization. Run Lighthouse audit command Configure LiteSpeed Cache (all sites use it) command Image optimization check Font and render-blocking resource optimization check Verify improvements and monitor command. Tags: seo, speed, performance, core-web-vitals, litespeed, images, caching' - 'SSL Certificate & Domain Management. Check domain/SSL status via Hostinger command Manage DNS records command SSL certificate management manual Domain security audit command. Tags: ssl, domain, certificate, dns, hostinger, renewal' pipeline_tag: sentence-similarity library_name: sentence-transformers metrics: - pearson_cosine - spearman_cosine model-index: - name: SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2 results: - task: type: semantic-similarity name: Semantic Similarity dataset: name: empire eval type: empire-eval metrics: - type: pearson_cosine value: 0.5531234570199464 name: Pearson Cosine - type: spearman_cosine value: 0.5320495924169611 name: Spearman Cosine --- # SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). It maps sentences & paragraphs to a 384-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-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) - **Maximum Sequence Length:** 256 tokens - **Output Dimensionality:** 384 dimensions - **Similarity Function:** Cosine Similarity ### 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': 256, 'do_lower_case': False, 'architecture': 'BertModel'}) (1): Pooling({'word_embedding_dimension': 384, '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("WealthFromAI/empire-embed") # Run inference sentences = [ 'batch articles', 'Bulk Article Creation for a Site. Research topics and identify content gaps command Generate content outlines and briefs command Write content using ZimmWriter or scripts prompt Generate featured images for all articles command Publish articles and set featured images command. Tags: content, articles, bulk, wordpress, seo, publishing, zimmwriter', 'Site Speed & Core Web Vitals Optimization. Run Lighthouse audit command Configure LiteSpeed Cache (all sites use it) command Image optimization check Font and render-blocking resource optimization check Verify improvements and monitor command. Tags: seo, speed, performance, core-web-vitals, litespeed, images, caching', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 384] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities) # tensor([[1.0000, 0.7041, 0.2289], # [0.7041, 1.0000, 0.3787], # [0.2289, 0.3787, 1.0000]]) ``` ## Evaluation ### Metrics #### Semantic Similarity * Dataset: `empire-eval` * Evaluated with [EmbeddingSimilarityEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator) | Metric | Value | |:--------------------|:----------| | pearson_cosine | 0.5531 | | **spearman_cosine** | **0.532** | ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 333 training samples * Columns: sentence_0, sentence_1, and label * Approximate statistics based on the first 333 samples: | | sentence_0 | sentence_1 | label | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------| | type | string | string | float | | details | | | | * Samples: | sentence_0 | sentence_1 | label | |:-------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| | bootstrap project | Bootstrap a New Empire Project. Create project directory and initialize git command Create PROJECT_DNA.md command Create CLAUDE.md with project-specific config prompt Set up Python environment command Create initial git commit and push to GitHub command Register project in EMPIRE-BRAIN command. Tags: empire, project, bootstrap, setup, new | 1.0 | | update container | WordPress Site SEO Setup & Configuration. Verify RankMath SEO plugin is installed and activated check Configure RankMath general settings prompt Set up Schema markup patterns per post type prompt Configure robots.txt and sitemap command Set up internal linking structure prompt Configure affiliate link handling prompt. Tags: wordpress, seo, rankmath, schema, setup | 0.0 | | restart service | Full WordPress Site Health Audit. Check plugins — installed, active, and update status command Verify SEO configuration command Test page speed with Lighthouse command Security check — WordFence scan and login protection check Test REST API connectivity and credentials command Check Google Search Console for crawl errors and ranking prompt. Tags: wordpress, audit, seo, security, performance, plugins, health | 0.0 | * Loss: [CosineSimilarityLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters: ```json { "loss_fct": "torch.nn.modules.loss.MSELoss" } ``` ### Training Hyperparameters #### Non-Default Hyperparameters - `per_device_train_batch_size`: 16 - `num_train_epochs`: 5 - `eval_strategy`: steps - `per_device_eval_batch_size`: 16 - `multi_dataset_batch_sampler`: round_robin #### All Hyperparameters
Click to expand - `per_device_train_batch_size`: 16 - `num_train_epochs`: 5 - `max_steps`: -1 - `learning_rate`: 5e-05 - `lr_scheduler_type`: linear - `lr_scheduler_kwargs`: None - `warmup_steps`: 0 - `optim`: adamw_torch_fused - `optim_args`: None - `weight_decay`: 0.0 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `optim_target_modules`: None - `gradient_accumulation_steps`: 1 - `average_tokens_across_devices`: True - `max_grad_norm`: 1 - `label_smoothing_factor`: 0.0 - `bf16`: False - `fp16`: False - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: None - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `torch_compile`: False - `torch_compile_backend`: None - `torch_compile_mode`: None - `use_liger_kernel`: False - `liger_kernel_config`: None - `use_cache`: False - `neftune_noise_alpha`: None - `torch_empty_cache_steps`: None - `auto_find_batch_size`: False - `log_on_each_node`: True - `logging_nan_inf_filter`: True - `include_num_input_tokens_seen`: no - `log_level`: passive - `log_level_replica`: warning - `disable_tqdm`: False - `project`: huggingface - `trackio_space_id`: trackio - `eval_strategy`: steps - `per_device_eval_batch_size`: 16 - `prediction_loss_only`: True - `eval_on_start`: False - `eval_do_concat_batches`: True - `eval_use_gather_object`: False - `eval_accumulation_steps`: None - `include_for_metrics`: [] - `batch_eval_metrics`: False - `save_only_model`: False - `save_on_each_node`: False - `enable_jit_checkpoint`: False - `push_to_hub`: False - `hub_private_repo`: None - `hub_model_id`: None - `hub_strategy`: every_save - `hub_always_push`: False - `hub_revision`: None - `load_best_model_at_end`: False - `ignore_data_skip`: False - `restore_callback_states_from_checkpoint`: False - `full_determinism`: False - `seed`: 42 - `data_seed`: None - `use_cpu`: False - `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 - `dataloader_drop_last`: False - `dataloader_num_workers`: 0 - `dataloader_pin_memory`: True - `dataloader_persistent_workers`: False - `dataloader_prefetch_factor`: None - `remove_unused_columns`: True - `label_names`: None - `train_sampling_strategy`: random - `length_column_name`: length - `ddp_find_unused_parameters`: None - `ddp_bucket_cap_mb`: None - `ddp_broadcast_buffers`: False - `ddp_backend`: None - `ddp_timeout`: 1800 - `fsdp`: [] - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} - `deepspeed`: None - `debug`: [] - `skip_memory_metrics`: True - `do_predict`: False - `resume_from_checkpoint`: None - `warmup_ratio`: None - `local_rank`: -1 - `prompts`: None - `batch_sampler`: batch_sampler - `multi_dataset_batch_sampler`: round_robin - `router_mapping`: {} - `learning_rate_mapping`: {}
### Training Logs | Epoch | Step | empire-eval_spearman_cosine | |:-----:|:----:|:---------------------------:| | 1.0 | 21 | 0.5320 | ### Framework Versions - Python: 3.12.10 - Sentence Transformers: 5.3.0 - Transformers: 5.4.0 - PyTorch: 2.11.0+cpu - Accelerate: 1.13.0 - Datasets: 4.8.4 - Tokenizers: 0.22.2 ## 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", } ```