metadata

language: []
library_name: sentence-transformers
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:300000
  - loss:DenoisingAutoEncoderLoss
base_model: intfloat/e5-base-unsupervised
datasets: []
metrics:
  - pearson_cosine
  - spearman_cosine
  - pearson_manhattan
  - spearman_manhattan
  - pearson_euclidean
  - spearman_euclidean
  - pearson_dot
  - spearman_dot
  - pearson_max
  - spearman_max
widget:
  - source_sentence: >-
      One mole of a substance of substance such atoms or). The is known or
      Avogadro's constant
    sentences:
      - how effective are birth control pills and pulling out?
      - can pvc be phthalate free?
      - >-
        One mole of a substance is equal to 6.022 × 10²³ units of that substance
        (such as atoms, molecules, or ions). The number 6.022 × 10²³ is known as
        Avogadro's number or Avogadro's constant.
  - source_sentence: >-
      is the difference between disability broadly defined a or to be
      significantly impaired relative to the standard an individual group . To
      the term disabled still just more, this or function
    sentences:
      - >-
        how to open pkf format? On a Windows PC, right-click the file, click
        "Properties", then look under “Type of File.” On a Mac computer,
        right-click the file, click “More Info,” then look under “Kind”. Tip: If
        it's the PKF file extension, it probably falls under the Audio Files
        type, so any program used for Audio Files should open your PKF file.
      - >-
        When someone dreams you died, it means that whatever you mean to that
        person's psychological state of mind 'has ended' or 'is absent'. ...
        People dream of dead people because they miss something about them that
        was very strong emotionally present when they were there, yet is missing
        in their daily-life now.
      - >-
        what is the difference between disability and disabled? A disability is
        broadly defined as a condition or function judged to be significantly
        impaired relative to the usual standard of an individual or group. ...
        To most people today the term "disabled" still means just that, and,
        more broadly, means "unable to perform" this or that physical or mental
        function.
  - source_sentence: how you contagious when
    sentences:
      - how long are you contagious when you have rsv?
      - >-
        With WiFi on your camera you establish a wireless connection between
        your camera and your phone, tablet, computer, or printer. It's also
        possible to connect two cameras with each other via WiFi. The camera has
        its own WiFi network that transmits signals.
      - >-
        So, what does it mean when a guy looks you up and down? It will often
        mean that he is checking you out especially if he only does it to you
        and he shows other signs of attraction when around you. It can also be
        that he is initially observing to see if you're a threat or that he is
        observing your outfit.
  - source_sentence: >-
      you light east while is you can the of the . understanding The on left is
      basically fajr time black you
    sentences:
      - >-
        A future - contract to buy (or sell) something in the future. An option
        - right BUT NOT the obligation to buy (or sell) something in the future.
        A swap - two parties exchanging something at agreed points in time. This
        could be an exchange of currencies, of returns on assets, of different
        interest rate returns, etc..
      - >-
        can i connect my iphone to my windows laptop? You can sync an iPhone
        with a Windows 10 computer wirelessly (over your local WiFi network) or
        via the Lightning cable. ... Open iTunes in Windows 10. Plug your iPhone
        (or iPad or iPod) into the computer using a Lightning cable (or older
        30-pin connector). Click on Device in iTunes and choose your iPhone.
      - >-
        Yes, Fajr is when you can see the light in the east while Sunrise is
        when you can see the disk of the sun. For those who have a trouble
        understanding: The blue area on the left is basically fajr time. The
        black area is when you can eat.
  - source_sentence: >-
      should eat diarrhea should solid as soon able you're bottle your have, try
      to them as . at home until 48 last spreading others.
    sentences:
      - >-
        which countries were not affected by world war 2? There were eight
        countries that declared neutrality; Portugal, Switzerland, Spain,
        Sweden, The Vatican, Andorra, Ireland and Liechtenstein. However, all of
        these countries were still involved in small ways.
      - how to copy multiple cells in excel and paste?
      - >-
        how long should you wait to eat after having diarrhea? You should eat
        solid food as soon as you feel able to. If you're breastfeeding or
        bottle feeding your baby and they have diarrhoea, you should try to feed
        them as normal. Stay at home until at least 48 hours after the last
        episode of diarrhoea to prevent spreading any infection to others.
pipeline_tag: sentence-similarity
model-index:
  - name: SentenceTransformer based on intfloat/e5-base-unsupervised
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.7707098586060571
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7583632499035035
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7590199401674214
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.747524480818435
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.760482148803808
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.7488744991502696
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5774036226110284
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5600384269062831
            name: Spearman Dot
          - type: pearson_max
            value: 0.7707098586060571
            name: Pearson Max
          - type: spearman_max
            value: 0.7583632499035035
            name: Spearman Max

SentenceTransformer based on intfloat/e5-base-unsupervised

This is a sentence-transformers model finetuned from intfloat/e5-base-unsupervised. 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: intfloat/e5-base-unsupervised
Maximum Sequence Length: 512 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': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (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("bobox/E5-base-unsupervised-TSDAE")
# Run inference
sentences = [
    "should eat diarrhea should solid as soon able you're bottle your have, try to them as . at home until 48 last spreading others.",
    "how long should you wait to eat after having diarrhea? You should eat solid food as soon as you feel able to. If you're breastfeeding or bottle feeding your baby and they have diarrhoea, you should try to feed them as normal. Stay at home until at least 48 hours after the last episode of diarrhoea to prevent spreading any infection to others.",
    'how to copy multiple cells in excel and paste?',
]
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]

Evaluation

Metrics

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.7707
spearman_cosine	0.7584
pearson_manhattan	0.759
spearman_manhattan	0.7475
pearson_euclidean	0.7605
spearman_euclidean	0.7489
pearson_dot	0.5774
spearman_dot	0.56
pearson_max	0.7707
spearman_max	0.7584

Training Details

Training Dataset

Unnamed Dataset

Size: 300,000 training samples
Columns: sentence_0 and sentence_1
Approximate statistics based on the first 1000 samples:
sentence_0 sentence_1
type string string
details
min: 3 tokens
mean: 20.46 tokens
max: 69 tokens

min: 8 tokens
mean: 47.85 tokens
max: 132 tokens

	sentence_0	sentence_1
type	string	string
details	min: 3 tokens mean: 20.46 tokens max: 69 tokens	min: 8 tokens mean: 47.85 tokens max: 132 tokens

Samples:

sentence_0	sentence_1
`matter An unit of retains all subatomic neutrons Hydrogen (one one neutrons`	`are particles of matter atoms? An atom is the smallest unit of matter that retains all of the chemical properties of an element. ... Most atoms contain all three of these types of subatomic particles—protons, electrons, and neutrons. Hydrogen (H) is an exception because it typically has one proton and one electron, but no neutrons.`
`equals how`	`5 ml equals how many ounces?`
`"A Country Boy School is poor is forced to its boy to school following official, ignoring mean a jail`	`"A Country Boy Quits School" by Lao Hsiang is an endearing social satire. It is about a poor Chinese family which is forced to send its boy to school following an official proclamation, ignoring which would mean a jail term.`

Loss: DenoisingAutoEncoderLoss

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 14
per_device_eval_batch_size: 14
num_train_epochs: 1
multi_dataset_batch_sampler: round_robin

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 14
per_device_eval_batch_size: 14
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: 1
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	sts-test_spearman_cosine
0	0	-	0.7211
0.0233	500	6.3144	-
0.0467	1000	5.3949	-
0.0500	1072	-	0.6820
0.0700	1500	5.0531	-
0.0933	2000	4.8547	-
0.1001	2144	-	0.7126
0.1167	2500	4.7058	-
0.1400	3000	4.5771	-
0.1501	3216	-	0.7290
0.1633	3500	4.4591	-
0.1867	4000	4.3502	-
0.2001	4288	-	0.7351
0.2100	4500	4.3071	-
0.2333	5000	4.2042	-
0.2501	5360	-	0.7464
0.2567	5500	4.1657	-
0.2800	6000	4.1111	-
0.3002	6432	-	0.7492
0.3033	6500	4.045	-
0.3267	7000	4.017	-
0.3500	7500	3.9651	-
0.3502	7504	-	0.7554
0.3733	8000	3.9199	-
0.3967	8500	3.8691	-
0.4002	8576	-	0.7517
0.4200	9000	3.8563	-
0.4433	9500	3.815	-
0.4502	9648	-	0.7540
0.4667	10000	3.7892	-
0.4900	10500	3.7543	-
0.5003	10720	-	0.7585
0.5133	11000	3.7391	-
0.5367	11500	3.7442	-
0.5503	11792	-	0.7587
0.5600	12000	3.7187	-
0.5833	12500	3.6855	-
0.6003	12864	-	0.7572
0.6067	13000	3.6751	-
0.6300	13500	3.6373	-
0.6503	13936	-	0.7574
0.6533	14000	3.6292	-
0.6767	14500	3.6277	-
0.7000	15000	3.6084	-
0.7004	15008	-	0.7575
0.7233	15500	3.6103	-
0.7467	16000	3.5953	-
0.7504	16080	-	0.7576
0.7700	16500	3.6232	-
0.7933	17000	3.5741	-
0.8004	17152	-	0.7583
0.8167	17500	3.5639	-
0.8400	18000	3.5667	-
0.8504	18224	-	0.7589
0.8633	18500	3.5598	-
0.8866	19000	3.5636	-
0.9005	19296	-	0.7584
0.9100	19500	3.5536	-
0.9333	20000	3.5529	-
0.9505	20368	-	0.7584
0.9566	20500	3.5485	-
0.9800	21000	3.5503	-
1.0	21429	-	0.7584

Framework Versions

Python: 3.10.13
Sentence Transformers: 3.0.1
Transformers: 4.41.2
PyTorch: 2.1.2
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",
}

DenoisingAutoEncoderLoss

@inproceedings{wang-2021-TSDAE,
    title = "TSDAE: Using Transformer-based Sequential Denoising Auto-Encoderfor Unsupervised Sentence Embedding Learning",
    author = "Wang, Kexin and Reimers, Nils and Gurevych, Iryna", 
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    pages = "671--688",
    url = "https://arxiv.org/abs/2104.06979",
}