metadata
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- dense
- generated_from_trainer
- dataset_size:6000
- loss:ContrastiveLoss
widget:
- source_sentence: ' "you only have minor depression \[I didn''t\], why are you acting so miserable?" Or by reminding me of the damage I was causing my loved ones like saying "you''re selfish, cruel and tearing this family apart'
sentences:
- ' (I have lost my period a couple more times in the past during my ED and in early recovery'
- ' I find myself angry when people keep commenting and questioning me about eating and weight loss!! At first I was angry because they were acting like I was starving myself, but now I''m seeing that maybe I am'
- ' My now two-year long treatment is already being held back by my attachment to my eating disorder, and I know a hospitalisation is just going trigger me into being more defensive of it'
- source_sentence: Over the last two weeks or so, I have developed severe and sudden anxiety
sentences:
- ' I''ve gained weight because of it, and struggling to deal with it a little'
- |2-
If you or someone you know qualifies, I would very much appreciate your or their input!
Participation is anonymous and completely voluntary
- ' I also started to feel a lot worse about my body and would try to go a really long time without eating'
- source_sentence: ' then he tried to convince me he messed with my scale to make it appear as if i maintained my weight, when really i yained 10 pounds ? i left after that'
sentences:
- >2-
What I need to know is this likely to become a serious eating disorder, or can I fix it with a schedule and some discipline?
Okay, so I have severe chronic migraines, so a lot of time eating
normally isn't an option for neurological reasons
- >-
Hey! I'm 16 and I don't know exactly if this is a specific ED (I'd love
to know if it is) but I've been havig trouble with food lately
- ' However, they were EXTREMELY unhelpful - discounting my feelings and suggesting that the only tried and true solution I needed was to lose weight healthily'
- source_sentence: ' I then went back to restricting, much more intensely with a much lower calorie limit'
sentences:
- ' This persists after I eat if I don''t eat until I feel full/satisfied, so I feel I need to keep eating a lot more than is recommended for someone of my size/activity level just so I can concentrate on my work'
- >2-
Obviously I have never followed through with it and still eat a very
consistent amount of food (sweets, etc
- >-
Which struck me as odd, because I have been underweight for as long as I
can remember, and yet no doctor has ever expressed concerns about it
- source_sentence: ' still has a lot of food fears, incredibly picky regardless and lots of food anxiety\* this is important'
sentences:
- ' I''ve been trying to keep down breakfast and supper everyday plus some snacks and I don''t think it''s enough but I don''t know if I''d be able to recover if I was eating any more than that'
- ' My relationship with food was much different in high school, I would eat without even thinking about it'
- ' I''ve never had an okay relationship with food and I don''t really know how to restrict without over-restricting'
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy
- cosine_accuracy_threshold
- cosine_f1
- cosine_f1_threshold
- cosine_precision
- cosine_recall
- cosine_ap
- cosine_mcc
model-index:
- name: SentenceTransformer
results:
- task:
type: binary-classification
name: Binary Classification
dataset:
name: quora duplicates dev
type: quora_duplicates_dev
metrics:
- type: cosine_accuracy
value: 0.7276315789473684
name: Cosine Accuracy
- type: cosine_accuracy_threshold
value: 0.6381747126579285
name: Cosine Accuracy Threshold
- type: cosine_f1
value: 0.6510989010989011
name: Cosine F1
- type: cosine_f1_threshold
value: 0.3570553660392761
name: Cosine F1 Threshold
- type: cosine_precision
value: 0.5738498789346247
name: Cosine Precision
- type: cosine_recall
value: 0.7523809523809524
name: Cosine Recall
- type: cosine_ap
value: 0.7166460442597221
name: Cosine Ap
- type: cosine_mcc
value: 0.35294907796969793
name: Cosine Mcc
SentenceTransformer
This is a sentence-transformers model trained. It maps sentences & paragraphs to a 1024-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
- Maximum Sequence Length: 256 tokens
- Output Dimensionality: 1024 dimensions
- 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': 256, 'do_lower_case': False, 'architecture': 'RobertaModel'})
(1): Pooling({'word_embedding_dimension': 1024, '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:
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("sentence_transformers_model_id")
# Run inference
sentences = [
' still has a lot of food fears, incredibly picky regardless and lots of food anxiety\\* this is important',
' My relationship with food was much different in high school, I would eat without even thinking about it',
" I've been trying to keep down breakfast and supper everyday plus some snacks and I don't think it's enough but I don't know if I'd be able to recover if I was eating any more than that",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.6203, 0.5744],
# [0.6203, 1.0000, 0.7722],
# [0.5744, 0.7722, 1.0000]])
Evaluation
Metrics
Binary Classification
- Dataset:
quora_duplicates_dev - Evaluated with
BinaryClassificationEvaluator
| Metric | Value |
|---|---|
| cosine_accuracy | 0.7276 |
| cosine_accuracy_threshold | 0.6382 |
| cosine_f1 | 0.6511 |
| cosine_f1_threshold | 0.3571 |
| cosine_precision | 0.5738 |
| cosine_recall | 0.7524 |
| cosine_ap | 0.7166 |
| cosine_mcc | 0.3529 |
Training Details
Training Dataset
Unnamed Dataset
- Size: 6,000 training samples
- Columns:
sentence1,sentence2, andlabel - Approximate statistics based on the first 1000 samples:
sentence1 sentence2 label type string string int details - min: 4 tokens
- mean: 33.52 tokens
- max: 169 tokens
- min: 5 tokens
- mean: 32.67 tokens
- max: 228 tokens
- 0: ~57.10%
- 1: ~42.90%
- Samples:
sentence1 sentence2 label Obviously as my age is specified there's not much I can do from a physical standpoint other than cook for her when I'm with her, but I'e been there for her emotionally in the past for other things and I think it helped herany advice would be greatly appreciated to help her1I am 15 years old and recently I have been feeling awful about it and realized how much of a problem it has become
And I know the answer is probably, "go see a doctor or therapist/talk to ur parents" however I'm worried about doing that since what if it's nothing but me worrying and making a deal about nothing, I don't want them judging me over something potentially stupid like this0This is Part 1 of 2 for 1 post) A friend asked me for some advice for her sister who is currently struggling with her relationship to food and her body
The things I'm concerned about:
- I don't like eating, I try to avoid it until my stomach physically hurts, especially when I have a major depressive episode1 - Loss:
ContrastiveLosswith these parameters:{ "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", "margin": 1.0, "size_average": true }
Evaluation Dataset
Unnamed Dataset
- Size: 760 evaluation samples
- Columns:
sentence1,sentence2, andlabel - Approximate statistics based on the first 760 samples:
sentence1 sentence2 label type string string int details - min: 4 tokens
- mean: 33.98 tokens
- max: 230 tokens
- min: 4 tokens
- mean: 31.82 tokens
- max: 192 tokens
- 0: ~58.55%
- 1: ~41.45%
- Samples:
sentence1 sentence2 label I'm not getting enough nutrients ?
I have a lot of unhealthy coping mechanisms and I'm trying to not SH as much anymore, which makes that the ED is coming up much stronger?
I don't know what to do or how to stop this, anyone have any advice?
Edit: I also have to say that when I eat I get really nauseous, but when I don't eat I also get nauseous, which then makes it harder to eat and it just keeps going on like thatI want to be smaller than them and all that because eds are like that, but that's hard when they don't tell me stuff and I'm left to stew in my own thoughts0I'm underweight right now and I was actually gaining weight since I was an average weight about two-three weeks ago and went downSo, this is definetly going into the right direction, but:
I am so afraid of stepping on the scale and seeing gained weight1I feel so much shame around the idea of eating junk food and often times, when things have gotten worse, part of that mechanism has been my definition of "junk food" getting so warped that I consider almost anything unhealthy and shameful to eatOverall, I realized my eating disorders had almost nothing to do with food0 - Loss:
ContrastiveLosswith these parameters:{ "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", "margin": 1.0, "size_average": true }
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy: stepsper_device_train_batch_size: 16per_device_eval_batch_size: 16gradient_accumulation_steps: 2learning_rate: 1.5e-05num_train_epochs: 5warmup_ratio: 0.1bf16: Truebatch_sampler: no_duplicates
All Hyperparameters
Click to expand
overwrite_output_dir: Falsedo_predict: Falseeval_strategy: stepsprediction_loss_only: Trueper_device_train_batch_size: 16per_device_eval_batch_size: 16per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 2eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 1.5e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 5max_steps: -1lr_scheduler_type: linearlr_scheduler_kwargs: {}warmup_ratio: 0.1warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Truefp16: Falsefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Falseignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torchoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Falseresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Nonehub_always_push: Falsegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseinclude_for_metrics: []eval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Nonedispatch_batches: Nonesplit_batches: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseuse_liger_kernel: Falseeval_use_gather_object: Falseaverage_tokens_across_devices: Falseprompts: Nonebatch_sampler: no_duplicatesmulti_dataset_batch_sampler: proportionalrouter_mapping: {}learning_rate_mapping: {}
Training Logs
| Epoch | Step | Training Loss | Validation Loss | quora_duplicates_dev_cosine_ap |
|---|---|---|---|---|
| 0.5333 | 100 | 0.2145 | - | - |
| 1.064 | 200 | 0.185 | 0.0903 | - |
| 1.5973 | 300 | 0.1472 | - | - |
| 2.128 | 400 | 0.1361 | 0.0914 | - |
| 2.6613 | 500 | 0.1045 | - | - |
| 3.192 | 600 | 0.0879 | 0.0957 | - |
| 3.7253 | 700 | 0.067 | - | - |
| 4.256 | 800 | 0.0617 | 0.1003 | - |
| 4.7893 | 900 | 0.0529 | - | - |
| -1 | -1 | - | - | 0.7166 |
Framework Versions
- Python: 3.10.8
- Sentence Transformers: 5.0.0
- Transformers: 4.49.0
- PyTorch: 2.1.2+cu118
- Accelerate: 1.4.0
- Datasets: 3.3.2
- Tokenizers: 0.21.0
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",
}
ContrastiveLoss
@inproceedings{hadsell2006dimensionality,
author={Hadsell, R. and Chopra, S. and LeCun, Y.},
booktitle={2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)},
title={Dimensionality Reduction by Learning an Invariant Mapping},
year={2006},
volume={2},
number={},
pages={1735-1742},
doi={10.1109/CVPR.2006.100}
}