metadata

language: []
library_name: sentence-transformers
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:1746
  - loss:CosineSimilarityLoss
base_model: sentence-transformers/distilbert-base-nli-mean-tokens
datasets: []
widget:
  - source_sentence: >-
      Scalloped Corn ["1 can cream-style corn", "1 can whole kernel corn", "1/2
      pkg. (approximately 20) saltine crackers, crushed", "1 egg, beaten", "6
      tsp. butter, divided", "pepper to taste"] ["Mix together both cans of
      corn, crackers, egg, 2 teaspoons of melted butter and pepper and place in
      a buttered baking dish.", "Dot with remaining 4 teaspoons of butter.",
      "Bake at 350\u00b0 for 1 hour."]
    sentences:
      - >-
        Artichoke Dip ["2 cans or jars artichoke hearts", "1 c. mayonnaise", "1
        c. Parmesan cheese"] ["Drain artichokes and chop.", "Mix with mayonnaise
        and Parmesan cheese.", "After well mixed, bake, uncovered, for 20 to 30
        minutes at 350\u00b0.", "Serve with crackers."]
      - >-
        Scalloped Corn ["1 can cream-style corn", "1 can whole kernel corn",
        "1/2 pkg. (approximately 20) saltine crackers, crushed", "1 egg,
        beaten", "6 tsp. butter, divided", "pepper to taste"] ["Mix together
        both cans of corn, crackers, egg, 2 teaspoons of melted butter and
        pepper and place in a buttered baking dish.", "Dot with remaining 4
        teaspoons of butter.", "Bake at 350\u00b0 for 1 hour."]
      - >-
        Chicken Stew ["3 lb. chicken, boiled", "4 medium potatoes, diced", "2
        medium onions, chopped", "1 (16 oz.) can creamed corn", "1 (16 oz.) can
        English peas", "1 (16 oz.) can field peas", "1 (16 oz.) can butter
        beans", "1 (16 oz.) can tomatoes", "1 (46 oz.) can tomato juice", "1
        small box macaroni", "1 Tbsp. black pepper", "1 Tbsp. salt", "1 Tbsp.
        sugar"] ["Remove chicken from bone.", "Use the broth.", "Mix the
        vegetables and macaroni.", "Add sugar, salt and black pepper.", "Cook
        until all vegetables are tender over medium heat."]
  - source_sentence: >-
      Watermelon Rind Pickles ["7 lb. watermelon rind", "7 c. sugar", "2 c.
      apple vinegar", "1/2 tsp. oil of cloves", "1/2 tsp. oil of cinnamon"]
      ["Trim off green and pink parts of watermelon rind; cut to 1-inch cubes.",
      "Parboil until tender, but not soft.", "Drain. Combine sugar, vinegar, oil
      of cloves and oil of cinnamon; bring to boiling and pour over rind.", "Let
      stand overnight.", "In the morning, drain off syrup.", "Heat and put over
      rind.", "The third morning, heat rind and syrup; seal in hot, sterilized
      jars.", "Makes 8 pints.", "(Oil of cinnamon and clove keeps rind clear and
      transparent.)"]
    sentences:
      - >-
        Cheeseburger Potato Soup ["6 baking potatoes", "1 lb. of extra lean
        ground beef", "2/3 c. butter or margarine", "6 c. milk", "3/4 tsp.
        salt", "1/2 tsp. pepper", "1 1/2 c (6 oz.) shredded Cheddar cheese,
        divided", "12 sliced bacon, cooked, crumbled and divided", "4 green
        onion, chopped and divided", "1 (8 oz.) carton sour cream (optional)"]
        ["Wash potatoes; prick several times with a fork.", "Microwave them with
        a wet paper towel covering the potatoes on high for 6-8 minutes.", "The
        potatoes should be soft, ready to eat.", "Let them cool enough to
        handle.", "Cut in half lengthwise; scoop out pulp and reserve.",
        "Discard shells.", "Brown ground beef until done.", "Drain any grease
        from the meat.", "Set aside when done.", "Meat will be added later.",
        "Melt butter in a large kettle over low heat; add flour, stirring until
        smooth.", "Cook 1 minute, stirring constantly. Gradually add milk; cook
        over medium heat, stirring constantly, until thickened and bubbly.",
        "Stir in potato, ground beef, salt, pepper, 1 cup of cheese, 2
        tablespoons of green onion and 1/2 cup of bacon.", "Cook until heated
        (do not boil).", "Stir in sour cream if desired; cook until heated (do
        not boil).", "Sprinkle with remaining cheese, bacon and green onions."]
      - >-
        Easy Fudge ["1 (14 oz.) can sweetened condensed milk", "1 (12 oz.) pkg.
        semi-sweet chocolate chips", "1 (1 oz.) sq. unsweetened chocolate (if
        desired)", "1 1/2 c. chopped nuts (if desired)", "1 tsp. vanilla"]
        ["Butter a square pan, 8 x 8 x 2-inches.", "Heat milk, chocolate chips
        and unsweetened chocolate over low heat, stirring constantly, until
        chocolate is melted and mixture is smooth. Remove from heat.", "Stir in
        nuts and vanilla.", "Spread in pan."]
      - >-
        Chicken Ole ["4 chicken breasts, cooked", "1 can cream of chicken soup",
        "1 can cream of mushroom soup", "1 can green chili salsa sauce", "1 can
        green chilies", "1 c. milk", "1 grated onion", "1 pkg. corn tortilla in
        pieces"] ["Dice chicken.", "Mix all ingredients together.", "Let sit
        overnight.", "Bake 1 1/2 hours at 375\u00b0."]
  - source_sentence: >-
      Quick Barbecue Wings ["chicken wings (as many as you need for dinner)",
      "flour", "barbecue sauce (your choice)"] ["Clean wings.", "Flour and fry
      until done.", "Place fried chicken wings in microwave bowl.", "Stir in
      barbecue sauce.", "Microwave on High (stir once) for 4 minutes."]
    sentences:
      - >-
        Creamy Corn ["2 (16 oz.) pkg. frozen corn", "1 (8 oz.) pkg. cream
        cheese, cubed", "1/3 c. butter, cubed", "1/2 tsp. garlic powder", "1/2
        tsp. salt", "1/4 tsp. pepper"] ["In a slow cooker, combine all
        ingredients. Cover and cook on low for 4 hours or until heated through
        and cheese is melted. Stir well before serving. Yields 6 servings."]
      - >-
        Broccoli Salad ["1 large head broccoli (about 1 1/2 lb.)", "10 slices
        bacon, cooked and crumbled", "5 green onions, sliced or 1/4 c. chopped
        red onion", "1/2 c. raisins", "1 c. mayonnaise", "2 Tbsp. vinegar", "1/4
        c. sugar"] ["Trim off large leaves of broccoli and remove the tough ends
        of lower stalks. Wash the broccoli thoroughly. Cut the florets and stems
        into bite-size pieces. Place in a large bowl. Add bacon, onions and
        raisins. Combine remaining ingredients, stirring well. Add dressing to
        broccoli mixture and toss gently. Cover and refrigerate 2 to 3 hours.
        Makes about 6 servings."]
      - >-
        Vegetable-Burger Soup ["1/2 lb. ground beef", "2 c. water", "1 tsp.
        sugar", "1 pkg. Cup-a-Soup onion soup mix (dry)", "1 lb. can stewed
        tomatoes", "1 (8 oz.) can tomato sauce", "1 (10 oz.) pkg. frozen mixed
        vegetables"] ["Lightly brown beef in soup pot.", "Drain off excess
        fat.", "Stir in tomatoes, tomato sauce, water, frozen vegetables, soup
        mix and sugar.", "Bring to a boil.", "Reduce heat and simmer for 20
        minutes. Serve."]
  - source_sentence: >-
      Eggless Milkless Applesauce Cake ["3/4 c. sugar", "1/2 c. shortening", "1
      1/2 c. applesauce", "3 level tsp. soda", "1 tsp. each: cinnamon, cloves
      and nutmeg", "2 c. sifted flour", "1 c. raisins", "1 c. nuts"] ["Mix
      Crisco with applesauce, nuts and raisins.", "Sift dry ingredients and
      add.", "Mix well.", "Put in a greased and floured loaf pan or tube pan.",
      "Bake in loaf pan at 350\u00b0 to 375\u00b0 for 45 to 60 minutes, layer
      pan at 375\u00b0 for 20 minutes or tube pan at 325\u00b0 for 1 hour."]
    sentences:
      - >-
        Broccoli Dip For Crackers ["16 oz. sour cream", "1 pkg. dry vegetable
        soup mix", "10 oz. pkg. frozen chopped broccoli, thawed and drained", "4
        to 6 oz. Cheddar cheese, grated"] ["Mix together sour cream, soup mix,
        broccoli and half of cheese.", "Sprinkle remaining cheese on top.",
        "Bake at 350\u00b0 for 30 minutes, uncovered.", "Serve hot with
        vegetable crackers."]
      - >-
        Potato And Cheese Pie ["3 eggs", "1 tsp. salt", "1/4 tsp. pepper", "2 c.
        half and half", "3 c. potatoes, shredded coarse", "1 c. Cheddar cheese,
        coarsely shredded", "1/3 c. green onions"] ["Beat eggs, salt and pepper
        until well blended.", "Stir in half and half, potatoes and onions.",
        "Pour into well-greased 8-inch baking dish.", "Bake in a 400\u00b0 oven
        for 35 to 40 minutes, or until knife inserted in center comes out clean
        and potatoes are tender. Cool on rack 5 minutes; cut into squares.",
        "Makes 4 large servings."]
      - >-
        Angel Biscuits ["5 c. flour", "3 Tbsp. sugar", "4 tsp. baking powder",
        "1 1/2 pkg. dry yeast", "2 c. buttermilk", "1 tsp. soda", "1 1/2 sticks
        margarine", "1/2 c. warm water"] ["Mix flour, sugar, baking powder, soda
        and salt together.", "Cut in margarine, dissolve yeast in warm water.",
        "Stir into buttermilk and add to dry mixture.", "Cover and chill."]
  - source_sentence: >-
      Rhubarb Coffee Cake ["1 1/2 c. sugar", "1/2 c. butter", "1 egg", "1 c.
      buttermilk", "2 c. flour", "1/2 tsp. salt", "1 tsp. soda", "1 c.
      buttermilk", "2 c. rhubarb, finely cut", "1 tsp. vanilla"] ["Cream sugar
      and butter.", "Add egg and beat well.", "To creamed butter, sugar and egg,
      add alternately buttermilk with mixture of flour, salt and soda.", "Mix
      well.", "Add rhubarb and vanilla.", "Pour into greased 9 x 13-inch pan and
      add Topping."]
    sentences:
      - >-
        Prize-Winning Meat Loaf ["1 1/2 lb. ground beef", "1 c. tomato juice",
        "3/4 c. oats (uncooked)", "1 egg, beaten", "1/4 c. chopped onion", "1/4
        tsp. pepper", "1 1/2 tsp. salt"] ["Mix well.", "Press firmly into an 8
        1/2 x 4 1/2 x 2 1/2-inch loaf pan.", "Bake in preheated moderate oven.",
        "Bake at 350\u00b0 for 1 hour.", "Let stand 5 minutes before slicing.",
        "Makes 8 servings."]
      - >-
        Angel Biscuits ["5 c. flour", "3 Tbsp. sugar", "4 tsp. baking powder",
        "1 1/2 pkg. dry yeast", "2 c. buttermilk", "1 tsp. soda", "1 1/2 sticks
        margarine", "1/2 c. warm water"] ["Mix flour, sugar, baking powder, soda
        and salt together.", "Cut in margarine, dissolve yeast in warm water.",
        "Stir into buttermilk and add to dry mixture.", "Cover and chill."]
      - >-
        Smothered Round Steak(Servings: 4)   ["2 lb. round steak", "1/2 tsp.
        ground black pepper", "1 tsp. ground white pepper", "1/2 c. vegetable
        oil", "2 bell peppers, chopped", "1 c. beef stock or water", "2 tsp.
        salt", "1 tsp. ground red pepper", "all-purpose flour (dredging)", "3
        medium onions, chopped", "1 celery rib, chopped"] ["Alex Patout says,
        \"Smothering is a multipurpose Cajun technique that works wonders with
        everything from game to snap beans.", "It's similar to what the rest of
        the world knows as braising.", "The ingredients are briefly browned or
        sauteed, then cooked with a little liquid over a low heat for a long
        time.\""]
pipeline_tag: sentence-similarity

SentenceTransformer based on sentence-transformers/distilbert-base-nli-mean-tokens

This is a sentence-transformers model finetuned from sentence-transformers/distilbert-base-nli-mean-tokens. 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/distilbert-base-nli-mean-tokens
Maximum Sequence Length: 128 tokens
Output Dimensionality: 768 tokens
Similarity Function: Cosine Similarity

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': 128, 'do_lower_case': False}) with Transformer model: DistilBertModel 
  (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("DivyaMereddy007/RecipeBert_v5original_epoc50_Copy_of_TrainSetenceTransforme-Finetuning_v5_DistilledBert")
# Run inference
sentences = [
    'Rhubarb Coffee Cake ["1 1/2 c. sugar", "1/2 c. butter", "1 egg", "1 c. buttermilk", "2 c. flour", "1/2 tsp. salt", "1 tsp. soda", "1 c. buttermilk", "2 c. rhubarb, finely cut", "1 tsp. vanilla"] ["Cream sugar and butter.", "Add egg and beat well.", "To creamed butter, sugar and egg, add alternately buttermilk with mixture of flour, salt and soda.", "Mix well.", "Add rhubarb and vanilla.", "Pour into greased 9 x 13-inch pan and add Topping."]',
    'Prize-Winning Meat Loaf ["1 1/2 lb. ground beef", "1 c. tomato juice", "3/4 c. oats (uncooked)", "1 egg, beaten", "1/4 c. chopped onion", "1/4 tsp. pepper", "1 1/2 tsp. salt"] ["Mix well.", "Press firmly into an 8 1/2 x 4 1/2 x 2 1/2-inch loaf pan.", "Bake in preheated moderate oven.", "Bake at 350\\u00b0 for 1 hour.", "Let stand 5 minutes before slicing.", "Makes 8 servings."]',
    'Angel Biscuits ["5 c. flour", "3 Tbsp. sugar", "4 tsp. baking powder", "1 1/2 pkg. dry yeast", "2 c. buttermilk", "1 tsp. soda", "1 1/2 sticks margarine", "1/2 c. warm water"] ["Mix flour, sugar, baking powder, soda and salt together.", "Cut in margarine, dissolve yeast in warm water.", "Stir into buttermilk and add to dry mixture.", "Cover and chill."]',
]
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: 1,746 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	float
details	min: 63 tokens mean: 119.05 tokens max: 128 tokens	min: 63 tokens mean: 118.49 tokens max: 128 tokens	min: 0.0 mean: 0.19 max: 1.0

Samples:

sentence_0	sentence_1	label
`Strawberry Whatever ["1 lb. frozen strawberries in juice", "1 small can crushed pineapple", "3 ripe bananas", "1 c. chopped pecans", "1 large pkg. strawberry Jell-O", "1 1/2 c. boiling water", "1 pt. sour cream"] ["Mix Jell-O in boiling water.", "Add strawberries, pineapple, crushed bananas and nuts.", "Spread 1/2 mixture in 13 x 6 1/2-inch pan.", "Allow to gel in freezer 30 minutes.", "Add layer of sour cream, then remaining mixture on top.", "Gel and serve."]`	One Hour Rolls ["1 c. milk", "2 Tbsp. sugar", "1 pkg. dry yeast", "1 Tbsp. salt", "3 Tbsp. Crisco oil", "2 c. plain flour"] ["Put flour into a large mixing bowl.", "Combine sugar, milk, salt and oil in a saucepan and heat to boiling; remove from heat and let cool to lukewarm.", "Add yeast and mix well.", "Pour into flour and stir.", "Batter will be sticky.", "Roll out batter on a floured board and cut with biscuit cutter.", "Lightly brush tops with melted oleo and fold over.", "Place rolls on a cookie sheet, put in a warm place and let rise for 1 hour.", "Bake at 350\u00b0 for about 20 minutes. Yield: 2 1/2 dozen."]	`0.1`
`Broccoli Dip For Crackers ["16 oz. sour cream", "1 pkg. dry vegetable soup mix", "10 oz. pkg. frozen chopped broccoli, thawed and drained", "4 to 6 oz. Cheddar cheese, grated"] ["Mix together sour cream, soup mix, broccoli and half of cheese.", "Sprinkle remaining cheese on top.", "Bake at 350\u00b0 for 30 minutes, uncovered.", "Serve hot with vegetable crackers."]`	`Vegetable-Burger Soup ["1/2 lb. ground beef", "2 c. water", "1 tsp. sugar", "1 pkg. Cup-a-Soup onion soup mix (dry)", "1 lb. can stewed tomatoes", "1 (8 oz.) can tomato sauce", "1 (10 oz.) pkg. frozen mixed vegetables"] ["Lightly brown beef in soup pot.", "Drain off excess fat.", "Stir in tomatoes, tomato sauce, water, frozen vegetables, soup mix and sugar.", "Bring to a boil.", "Reduce heat and simmer for 20 minutes. Serve."]`	`0.4`
`Summer Spaghetti ["1 lb. very thin spaghetti", "1/2 bottle McCormick Salad Supreme (seasoning)", "1 bottle Zesty Italian dressing"] ["Prepare spaghetti per package.", "Drain.", "Melt a little butter through it.", "Marinate overnight in Salad Supreme and Zesty Italian dressing.", "Just before serving, add cucumbers, tomatoes, green peppers, mushrooms, olives or whatever your taste may want."]`	Chicken Funny ["1 large whole chicken", "2 (10 1/2 oz.) cans chicken gravy", "1 (10 1/2 oz.) can cream of mushroom soup", "1 (6 oz.) box Stove Top stuffing", "4 oz. shredded cheese"] ["Boil and debone chicken.", "Put bite size pieces in average size square casserole dish.", "Pour gravy and cream of mushroom soup over chicken; level.", "Make stuffing according to instructions on box (do not make too moist).", "Put stuffing on top of chicken and gravy; level.", "Sprinkle shredded cheese on top and bake at 350\u00b0 for approximately 20 minutes or until golden and bubbly."]	`0.3`

Loss: CosineSimilarityLoss with these parameters:

{
    "loss_fct": "torch.nn.modules.loss.MSELoss"
}

Training Hyperparameters

Non-Default Hyperparameters

per_device_train_batch_size: 16
per_device_eval_batch_size: 16
num_train_epochs: 50
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
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: 50
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: 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}
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: False
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
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
dispatch_batches: None
split_batches: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
batch_sampler: batch_sampler
multi_dataset_batch_sampler: round_robin

Training Logs

Epoch	Step	Training Loss
4.5455	500	0.0594
9.0909	1000	0.0099
13.6364	1500	0.0085
18.1818	2000	0.0077
22.7273	2500	0.0074
27.2727	3000	0.0071
31.8182	3500	0.0068
36.3636	4000	0.0066
40.9091	4500	0.0063
45.4545	5000	0.006
50.0	5500	0.0057

Framework Versions

Python: 3.10.12
Sentence Transformers: 3.0.1
Transformers: 4.41.2
PyTorch: 2.3.0+cu121
Accelerate: 0.31.0
Datasets: 2.19.2
Tokenizers: 0.19.1

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",
}