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+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:11180
+- loss:CosineSimilarityLoss
+widget:
+- source_sentence: '" My cousin said he share hoes with his brothers. He said sharing
+    is caring and he love his brothers 😂"'
+  sentences:
+  - Clerical Error Led to Costa Rica's First Legal Gay Marriage
+  - 'UPDATE: The leasing office is going to tape notes on ALL tenants doors in our
+    building as to not single anyone out. However, we were not the first to complain.
+    Our maintenance guy also caught them smoking in the breezeway of our building
+    and told them to cut it out. Hopefully the note helps, if not, I don''t care enough
+    to make it a bigger issue and I''m only here for the next 8 months so smoke em
+    if you got em I guess.
+
+
+    Alright bare/bear with me here...
+
+
+    My husband and I live in a pretty decent apartment complex, we''re on the top
+    floor, and we are cool with most of our neighbors. We''re 90% sure about which
+    neighbor is smoking the devils lettuce, as it only really started when our next-door
+    neighbors new roommate moved in.
+
+
+    I have nothing against smoking, in any capacity, but it''s literally all our apartment
+    has smelled like the last few months. It''s starting to permeate our clothes and
+    furniture it''s so bad. My husband and I both work for the government (and are
+    drug tested) so this is not ideal. At first (before we realized what was actually
+    going on) we thought a skunk had sprayed near our apartment and was just coming
+    in through a window. Well, it''s winter now, no windows are open, and every day
+    we wake up to and come home to SKUNK. We have told the apartment complex about
+    this, and nothing has changed.
+
+
+    WIBTA if I left a note on this neighbors door? Something to the effect of "Hey
+    fellow apartment dwellers, pot is fun. However, consider blowing the smoke out
+    into a paper towel roll that has a dryer sheet at the end. Or vape it. Or eat
+    it. My entire apartment smells like skunky pot and I''m over it. Love, your neighbors"
+
+
+    Thoughts?
+
+
+    Edit: When we messaged the complex about it, we didn''t single out them or their
+    apartment, just said "someone in our building." They actually have since responded
+    saying that they''d "send a message to our building about it," so we''ll see what
+    happens! I''ll hold off on the note/talking to them in person for now, but if
+    it continues I''m definitely considering buying two smoke buddies and wrapping
+    them up nicely in Christmas paper with a little (not aggressive) card.
+
+
+    Edit 2: Enough people are asking so I wanted to clarify, **I do not live in a
+    state where it is legal.**'
+  - 'And just as Kamala Harris is dedicated to building an America for all peoples,
+    so too am I.
+
+
+    That is why the idea that freedom of religion somehow comes primary is so offensive
+    to the very idea of an America for all.
+
+
+    Some religions will cite their bigotry as having a basis in scripture. That will
+    apply to bigotry hitting the LDS community as well.
+
+
+    According to Christian doctrine, [the LDS church is fundamentally heretical](
+
+
+    Without discrimination protections, a catholic, muslim, jewish or christian business
+    can discriminate against the members of the LDS church without recourse.
+
+
+    That is why the protection of anti-discrimination measures must inevitably step
+    on the toes of religious bigotry. Religion is cited to justify bigotry. Just as
+    it was by the LDS church.'
+- source_sentence: Thomson Buys Test Provider Capstar  TORONTO (Reuters) - Electronic
+    publisher Thomson Corp.  TOC.TO said on Monday it will buy test provider Capstar
+    from  Educational Testing Service, the latest in a string of  acquisitions designed
+    to flesh out its product offerings.
+  sentences:
+  - 'This is one of the most brilliant movies that I have seen in recent times. Goes
+    way above even any international movie of any repute. I am really surprised why
+    this has not received the recognition it deserved. Sonali Kulkarni winning the
+    National Award is perhaps the only consoling fact. Renuka Daftardar simply amazes
+    as she speaks volumes through her eyes. There are a few scenes that stand out:
+    When Gauri comes back from the city on Krishna''s wedding, she and Krishna meet
+    for the first time in many years. Krishna notices a change in Gauri, but not a
+    single line of dialogue is said. The entire gamut of emotions is conveyed through
+    subtle mannerisms and the eyes. There''s another towards the end when Krishna
+    pleads to Abhay Kulkarni to marry Gauri instead. If you are not moved by that
+    scene, you don''t have a heart.Watch this movie for sheer movie-making brilliance
+    and acting capabilities.'
+  - I put all my genius into my life I put only my talent into my works.
+  - '" we dont trust these niggas all these bitches "'
+- source_sentence: 'Project 2025 happens. We already know what will happen. The only
+    thing we don''t know his how quick Republican plan to burn things down.
+
+
+    I think they will move quick. The pointy hoods are off. Everything is being said
+    out loud. They have their own website for fucks sake.
+
+
+    "We''re going to make the country so successful again, I''m not going to have
+    time for retribution, and remember this: our ultimate retribution is success."
+    - Trump'
+  sentences:
+  - 'I have a stepdaughter who i have never gotten along with . There is only a three
+    year age difference, so I''m not entirely blaming her, but i think my husband
+    did a shitty job raising her. She is just not nice, and not just to me, but she
+    is rude to wait staff, entitled, something of a mean girl. She has always made
+    snide comments about our age difference and me being a gold digger because I quit
+    my job. I told her once as an April Fool''s joke that her dad was leaving me everything
+    in the will, and she didn''t even respond to me, she just tattled to daddy.
+
+
+    She graduated in May with a PhD, and before she realized that she wasn''t going
+    to have a graduation because of what''s going on right now, she made a big deal
+    of announcing to everyone that I wasn''t invited. My husband told me to just deal
+    with it, because it is her graduation.
+
+
+    She came over the other night with her boyfriend of three years (she''s 26 and
+    he is 38, important later) and announced that they are getting married. Honestly
+    I was kind of pissed off. My husband is wealthy, but her boyfriend is legit rich,
+    so she is doing exactly what I did, marrying a man with a large age gap, and marrying
+    a man with a lot of money. I''m not saying that she doesn''t love him, but I think
+    she is a huge hypocrite to not acknowledge that just maybe i love her dad.
+
+
+    I told her that was kind of hypocritical and ironic and she just rolled her eyes,
+    but after the fact my husband got mad and said I was trying to steal her spotlight
+    and make her engagement about me, but he is always super defensive about her.'
+  - Paul Hamm Wins All-Around Event After falling on the landing of his vault, Paul
+    Hamm put on two of the most spectacular routines of his career to win Olympic
+    gold, the first ever by a U.S. man.
+  - "This morning I (31m) woke up and it was cold as hell in my apartment. I didn't\
+    \ realize the weather was getting a little cooler today and didn't adjust the\
+    \ thermostat accordingly, I just left it on full blast all night since its been\
+    \ hot lately. I woke up in the morning and had to take a shower before work and\
+    \ the whole apartment was freezing. \n\nI wasn't really in the mood to be cold\
+    \ as hell and shivering when I got out of the shower and had to do my hair and\
+    \ all that, so after I cleaned myself off, I just stood towards the back of the\
+    \ shower and turned the water to as hot as it goes and let it run for about ten\
+    \ or fifteen minutes. After a couple minutes I opened the bathroom door to start\
+    \ letting the heat and steam out so it wouldn't be so cold. I got out of the shower\
+    \ and it was steamy as hell and so nice and comfortable. The bathroom mirror was\
+    \ all cloudy from the steam.\n\nWhile I was doing my hair my fiance comes in and\
+    \ asks why the apartment is so foggy, so I told her what I did. I figured it was\
+    \ no big deal but she made it seem like I was a huge dick for it, saying it's\
+    \ stupid and childish and a waste of water, but I really feel like she was overreacting\
+    \ and just looking for an argument or something. What do you guys think? AITA?"
+- source_sentence: Jake decides that the car would just need to be cleaned again in
+    the future so it would be a waste of time.
+  sentences:
+  - 'You guys think if I got a big face tattoo that said #metoo it would stop the
+    comments drunk men make at me while I do my job????'
+  - "please stop your oppressive editing\n TAB+TAB\nHi. I see that you're not as stupid\
+    \ as the other sysop, trying to block ip addresses and stuff. But all my warnings\
+    \ apply to you too. And if you're still wondering what this is about or who the\
+    \ fuck I am, you know what to do. Just do a whois on my ip117.201.39.75"
+  - Mindy cuts off ties with John and finds other friends who won't abuse her.
+- source_sentence: Besides that which the men brought him that were over the tributes,
+    and the merchants, and they that sold by retail, and all the kings of Arabia,
+    and the governors of the country.
+  sentences:
+  - I don't look for much to come out of government ownership as long as we have Democrats
+    and Republicans.
+  - If this needs a federal mandate and 100% global consensus, than leaders like Macron
+    should let us renegotiate. As it stands right now, this agreement is 100% toothless.
+    There are no penalties for not following through with it.
+  - 'Barclays to Buy CIBC Credit Card Unit for \$293 Mln (Update1) Aug. 18 (Bloomberg)
+    -- Barclays Plc, the UK #39;s third- biggest bank, agreed to buy Juniper Financial
+    Corp. from Canadian Imperial Bank of Commerce for \$293 million in cash to help
+    expand its credit card business in North America.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- pearson_cosine
+- spearman_cosine
+model-index:
+- name: SentenceTransformer
+  results:
+  - task:
+      type: semantic-similarity
+      name: Semantic Similarity
+    dataset:
+      name: similarity
+      type: similarity
+    metrics:
+    - type: pearson_cosine
+      value: 0.3879415946781869
+      name: Pearson Cosine
+    - type: spearman_cosine
+      value: 0.40484905925030346
+      name: Spearman Cosine
+---
+
+# SentenceTransformer
+
+This is a [sentence-transformers](https://www.SBERT.net) 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
+<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 1024 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/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': 512, 'do_lower_case': False, 'architecture': 'BertModel'})
+  (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:
+
+```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("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'Besides that which the men brought him that were over the tributes, and the merchants, and they that sold by retail, and all the kings of Arabia, and the governors of the country.',
+    'If this needs a federal mandate and 100% global consensus, than leaders like Macron should let us renegotiate. As it stands right now, this agreement is 100% toothless. There are no penalties for not following through with it.',
+    "I don't look for much to come out of government ownership as long as we have Democrats and Republicans.",
+]
+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, 0.5648, 0.5502],
+#         [0.5648, 1.0000, 0.7965],
+#         [0.5502, 0.7965, 1.0000]])
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Semantic Similarity
+
+* Dataset: `similarity`
+* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
+
+| Metric              | Value      |
+|:--------------------|:-----------|
+| pearson_cosine      | 0.3879     |
+| **spearman_cosine** | **0.4048** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 11,180 training samples
+* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                          | sentence_1                                                                         | label                                                          |
+  |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                              | string                                                                             | float                                                          |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 104.26 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 118.5 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.53</li><li>max: 1.0</li></ul> |
+* Samples:
+  | sentence_0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | sentence_1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | label                           |
+  |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------|
+  | <code>He worked at Rothschild as an investment banker. Great. Am I supposed to be alarmed that France elected a technocrat who has worked in the private banking sector? <br><br>I also don't give a shit about what macron does in his personal life. Clearly the French people don't either.</code>                                                                                                                                                                                                                                      | <code>Chad runs over the raccoon since it's been bothering him anyway.</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | <code>0.3535533905932737</code> |
+  | <code>Amazing effects for a movie of this time. A primer of the uselessness of war and how war becomes a nurturer of itself.A wonderful thing about this movie is it is now public domain and available at archive.org. No charge, no sign up necessary. Watch it in one sitting and you will be propelled.I plan to share this flick with as many people as possible as I had never heard of it before and I am a hard core sci fi fan.I would like to see how others react to this movie.Watch it.Rate it.Tell us what you think.</code> | <code>First off, I must say that I made the mistake of watching the Election films out of sequence. I say unfortunately, because after seeing Election 2 first, Election seems a bit of a disappointment. Both films are gangster epics that are similar in form. And while Election is an enjoyable piece of cinema... it's just not nearly as good as it's sequel.In the first Election installment, we are shown the two competitors for Chairman; Big D and Lok. After a few scenes of discussion amongst the "Uncle's" as to who should have the Chairman title, they (almost unanimously) decide That Lok (Simon Yam) will helm the Triads. Suffice to say this doesn't go over very well with competitor Big D (Tony Leung Ka Fai) and in a bid to influence the takeover, Big D kidnaps two of the uncles in order to sway the election board to his side. This has disastrous results and heads the triads into an all out war. Lok is determined to become Chairman but won't become official until he can recover the "Dragon Head ...</code> | <code>0.7071067811865475</code> |
+  | <code>MY SINCERE APOLOGIES 2U WHO I'VE OFFENDED WITH ALLEGATIONS OF COMPLACENT COWARDS & ASSHOLES FOR CLIMATE CHANGE INDIFFERENCE!</code>                                                                                                                                                                                                                                                                                                                                                                                                  | <code>yeah man fucking disgusting. as if we didn't waste enough time at work</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | <code>1.0</code>                |
+* Loss: [<code>CosineSimilarityLoss</code>](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
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 32
+- `per_device_eval_batch_size`: 32
+- `fp16`: True
+- `multi_dataset_batch_sampler`: round_robin
+
+#### 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`: 32
+- `per_device_eval_batch_size`: 32
+- `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`: 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`: 3
+- `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`: True
+- `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`: None
+- `hub_always_push`: False
+- `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
+- `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
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | similarity_spearman_cosine |
+|:------:|:----:|:-------------:|:--------------------------:|
+| 0.0286 | 10   | -             | 0.2006                     |
+| 0.0571 | 20   | -             | 0.2012                     |
+| 0.0857 | 30   | -             | 0.2023                     |
+| 0.1143 | 40   | -             | 0.2036                     |
+| 0.1429 | 50   | -             | 0.2054                     |
+| 0.1714 | 60   | -             | 0.2081                     |
+| 0.2    | 70   | -             | 0.2098                     |
+| 0.2286 | 80   | -             | 0.2115                     |
+| 0.2571 | 90   | -             | 0.2128                     |
+| 0.2857 | 100  | -             | 0.2149                     |
+| 0.3143 | 110  | -             | 0.2177                     |
+| 0.3429 | 120  | -             | 0.2207                     |
+| 0.3714 | 130  | -             | 0.2243                     |
+| 0.4    | 140  | -             | 0.2278                     |
+| 0.4286 | 150  | -             | 0.2310                     |
+| 0.4571 | 160  | -             | 0.2332                     |
+| 0.4857 | 170  | -             | 0.2350                     |
+| 0.5143 | 180  | -             | 0.2361                     |
+| 0.5429 | 190  | -             | 0.2360                     |
+| 0.5714 | 200  | -             | 0.2369                     |
+| 0.6    | 210  | -             | 0.2423                     |
+| 0.6286 | 220  | -             | 0.2533                     |
+| 0.6571 | 230  | -             | 0.2691                     |
+| 0.6857 | 240  | -             | 0.2808                     |
+| 0.7143 | 250  | -             | 0.2889                     |
+| 0.7429 | 260  | -             | 0.2960                     |
+| 0.7714 | 270  | -             | 0.2939                     |
+| 0.8    | 280  | -             | 0.3007                     |
+| 0.8286 | 290  | -             | 0.3010                     |
+| 0.8571 | 300  | -             | 0.3016                     |
+| 0.8857 | 310  | -             | 0.3035                     |
+| 0.9143 | 320  | -             | 0.3078                     |
+| 0.9429 | 330  | -             | 0.3138                     |
+| 0.9714 | 340  | -             | 0.3206                     |
+| 1.0    | 350  | -             | 0.3234                     |
+| 1.0286 | 360  | -             | 0.3299                     |
+| 1.0571 | 370  | -             | 0.3367                     |
+| 1.0857 | 380  | -             | 0.3267                     |
+| 1.1143 | 390  | -             | 0.3307                     |
+| 1.1429 | 400  | -             | 0.3359                     |
+| 1.1714 | 410  | -             | 0.3417                     |
+| 1.2    | 420  | -             | 0.3504                     |
+| 1.2286 | 430  | -             | 0.3324                     |
+| 1.2571 | 440  | -             | 0.3365                     |
+| 1.2857 | 450  | -             | 0.3580                     |
+| 1.3143 | 460  | -             | 0.3622                     |
+| 1.3429 | 470  | -             | 0.3073                     |
+| 1.3714 | 480  | -             | 0.3596                     |
+| 1.4    | 490  | -             | 0.3473                     |
+| 1.4286 | 500  | 0.1278        | 0.3573                     |
+| 1.4571 | 510  | -             | 0.3539                     |
+| 1.4857 | 520  | -             | 0.3355                     |
+| 1.5143 | 530  | -             | 0.3299                     |
+| 1.5429 | 540  | -             | 0.3559                     |
+| 1.5714 | 550  | -             | 0.3285                     |
+| 1.6    | 560  | -             | 0.3435                     |
+| 1.6286 | 570  | -             | 0.3654                     |
+| 1.6571 | 580  | -             | 0.3824                     |
+| 1.6857 | 590  | -             | 0.3426                     |
+| 1.7143 | 600  | -             | 0.3413                     |
+| 1.7429 | 610  | -             | 0.3395                     |
+| 1.7714 | 620  | -             | 0.3492                     |
+| 1.8    | 630  | -             | 0.3664                     |
+| 1.8286 | 640  | -             | 0.3634                     |
+| 1.8571 | 650  | -             | 0.3392                     |
+| 1.8857 | 660  | -             | 0.3686                     |
+| 1.9143 | 670  | -             | 0.3722                     |
+| 1.9429 | 680  | -             | 0.3557                     |
+| 1.9714 | 690  | -             | 0.3896                     |
+| 2.0    | 700  | -             | 0.3908                     |
+| 2.0286 | 710  | -             | 0.3859                     |
+| 2.0571 | 720  | -             | 0.3536                     |
+| 2.0857 | 730  | -             | 0.3606                     |
+| 2.1143 | 740  | -             | 0.3638                     |
+| 2.1429 | 750  | -             | 0.3713                     |
+| 2.1714 | 760  | -             | 0.3704                     |
+| 2.2    | 770  | -             | 0.3441                     |
+| 2.2286 | 780  | -             | 0.3435                     |
+| 2.2571 | 790  | -             | 0.3668                     |
+| 2.2857 | 800  | -             | 0.3735                     |
+| 2.3143 | 810  | -             | 0.3373                     |
+| 2.3429 | 820  | -             | 0.3474                     |
+| 2.3714 | 830  | -             | 0.3560                     |
+| 2.4    | 840  | -             | 0.3028                     |
+| 2.4286 | 850  | -             | 0.3485                     |
+| 2.4571 | 860  | -             | 0.3604                     |
+| 2.4857 | 870  | -             | 0.3769                     |
+| 2.5143 | 880  | -             | 0.3600                     |
+| 2.5429 | 890  | -             | 0.3916                     |
+| 2.5714 | 900  | -             | 0.3957                     |
+| 2.6    | 910  | -             | 0.3797                     |
+| 2.6286 | 920  | -             | 0.3875                     |
+| 2.6571 | 930  | -             | 0.3978                     |
+| 2.6857 | 940  | -             | 0.3951                     |
+| 2.7143 | 950  | -             | 0.3831                     |
+| 2.7429 | 960  | -             | 0.3912                     |
+| 2.7714 | 970  | -             | 0.3800                     |
+| 2.8    | 980  | -             | 0.3955                     |
+| 2.8286 | 990  | -             | 0.3976                     |
+| 2.8571 | 1000 | 0.1036        | 0.4048                     |
+
+
+### Framework Versions
+- Python: 3.11.9
+- Sentence Transformers: 5.1.0
+- Transformers: 4.49.0
+- PyTorch: 2.8.0+cu128
+- Accelerate: 1.10.0
+- Datasets: 2.14.4
+- Tokenizers: 0.21.0
+
+## 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",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "./models/pretrained/gte-large",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.1.0",
+    "transformers": "4.49.0",
+    "pytorch": "2.8.0+cu128"
+  },
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a846270ef79ec7517531a94c9d816903d7b59602b410352185a48014ca8d0128
+size 1340612432

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+    "max_seq_length": 512,
+    "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,63 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_length": 128,
+  "model_max_length": 512,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}