Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 128,
+  "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
+}

README.md

@@ -0,0 +1,487 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:8959
+- loss:CoSENTLoss
+base_model: prajjwal1/bert-tiny
+widget:
+- source_sentence: 'This card is treated as a Normal Monster while face-up on the
+    field or in the GY. While this card is face-up on the field, you can Normal Summon
+    it to have it become an Effect Monster with this effect. During your End Phase:
+    You can target 1 Equip Spell Card in your GY; add that target to your hand. You
+    can only use this effect of "Knight Day Grepher" once per turn.'
+  sentences:
+  - "2 Beast-Warrior monsters, including a WIND \"Ancient Warriors\" monster\r\nAll\
+    \ \"Ancient Warriors\" monsters you control gain 500 ATK/DEF. You can only use\
+    \ each of the following effects of \"Ancient Warriors Oath - Double Dragon Lords\"\
+    \ once per turn. If this card is Link Summoned: You can add 1 \"Ancient Warriors\"\
+    \ card from your Deck to your hand. (Quick Effect): You can send 1 card from your\
+    \ hand or field to the GY, then target 1 face-up card your opponent controls;\
+    \ return it to the hand."
+  - Place 1 Ocean Counter on this card during each player's Standby Phases. When this
+    card is removed from the field, all Fish-Type and Sea Serpent-Type monsters you
+    control gain 200 ATK for each Ocean Counter on this card, until the End Phase.
+  - 'If you have no cards in your GY (Quick Effect): You can send this card from your
+    hand to the GY; until the end of the next turn, any card sent to the GY is banished
+    instead.'
+- source_sentence: "Target 1 monster on the field or in either GY, then activate 1\
+    \ of these appropriate effects;\r\n● Attach the targeted monster to 1 Rank 2 monster\
+    \ you control as material.\r\n● Place the targeted monster your opponent controls\
+    \ in your zone your Link-2 monster points to, and take control of it.\r\n● Special\
+    \ Summon the targeted monster from either GY to your zone your Link-2 monster\
+    \ points to.\r\nYou can only activate 1 \"Spright Double Cross\" per turn."
+  sentences:
+  - '1 Level 1 monster When an opponent''s monster declares an attack: You can Tribute
+    this card; change that opponent''s monster''s ATK to 0, until the end of this
+    turn. If this card is in your GY (Quick Effect): You can Tribute 1 Level 1 monster;
+    Special Summon this card. You can only use this effect of "Linkuriboh" once per
+    turn.'
+  - This creature's wings are capable of generating tornadoes.
+  - 'You can target 1 monster you control with 0 ATK and 1 DARK Reptile monster in
+    your GY; destroy that monster on the field, and if you do, Special Summon the
+    other monster from your GY. If your opponent activates a monster effect: You can
+    target 1 face-up monster they control with 0 ATK; take control of it, then Special
+    Summon 1 "Reptilianne Token" (Reptile/EARTH/Level 1/ATK 0/DEF 0) to your opponent''s
+    field. You can only use each effect of "Reptilianne Recoil" once per turn.'
+- source_sentence: 'Add 1 LIGHT Machine monster that cannot be Normal Summoned/Set,
+    or 1 "Cyber Dragon" monster, from your Deck to your hand. If the activation of
+    this card in its owner''s possession was negated by your opponent''s card effect
+    and sent to your GY: You can discard 1 card; add this card to your hand. You can
+    only activate 1 "Cyberse Emergency" per turn.'
+  sentences:
+  - 'Cannot be destroyed by monster effects. You can only use each of the following
+    effects of "Shining Sarcophagus" once per turn. During your Main Phase: You can
+    add 1 card that mentions "Shining Sarcophagus" from your Deck to your hand, except
+    "Shining Sarcophagus". If your opponent Special Summons a monster(s) from the
+    GY (except during the Damage Step): You can discard 1 Spell, then target 1 of
+    those monsters; send it to the GY.'
+  - Activate only while all monsters on the field are face-up. Both players send monsters
+    they control to the GY so that they each control only 1 Attribute.
+  - 'When your opponent activates a Pendulum Monster''s effect, or an effect of a
+    card in the Pendulum Zone: Negate the activation, and if you do, banish that card.'
+- source_sentence: Fusion Summon 1 Fusion Monster from your Extra Deck, using monsters
+    from your hand or your side of the field as Fusion Materials.
+  sentences:
+  - "(This card is always treated as an \"Infernoble Knight\" card.)\r\nYou can discard\
+    \ this card, then target 1 Warrior monster you control; equip it with 1 Equip\
+    \ Spell from your Deck that can equip to it. When this card, not equipped with\
+    \ an Equip Card, is destroyed by battle with an opponent's monster and sent to\
+    \ the GY: You can Special Summon this card, and if you do, equip that monster\
+    \ your opponent controls to this card. You can only use each effect of \"Courageous\
+    \ Crimson Chevalier Bradamante\" once per turn."
+  - Destroy as many Normal Monsters on the field as possible, and if you do, Special
+    Summon Level 4 or lower Dinosaur-Type monsters from your Deck, up to the number
+    destroyed, but destroy them during the End Phase. You can banish this card from
+    your GY, then target 1 Dinosaur-Type monster you control and 1 card your opponent
+    controls; destroy them.
+  - '1 "Elemental HERO" monster + 1 WIND monster
+
+    Must be Fusion Summoned and cannot be Special Summoned by other ways. When this
+    card is Fusion Summoned: Halve the ATK and DEF of all face-up monsters your opponent
+    controls.'
+- source_sentence: '2 Cyberse monsters If this card is Link Summoned: You can add
+    1 "Cynet Fusion" from your Deck to your hand. If a monster(s) is Special Summoned
+    to a zone(s) this card points to (except during the Damage Step): You can target
+    1 Level 4 or lower Cyberse monster in your GY; Special Summon it, but negate its
+    effects, also you cannot Special Summon monsters from the Extra Deck for the rest
+    of this turn, except Fusion Monsters. You can only use each effect of "Clock Spartoi"
+    once per turn.'
+  sentences:
+  - You can banish 1 "Virtual World" card from your GY, then target 1 face-up monster
+    on the field; negate its effects until the end of this turn (even if this card
+    leaves the field). You can banish this card from your GY; add 1 "Virtual World"
+    monster from your Deck to your hand, then send 1 card from your hand to the GY.
+    You can only use each effect of "Virtual World Gate - Qinglong" once per turn.
+  - '(Quick Effect): You can Tribute 2 monsters, then target 1 of your Normal Traps
+    that is banished or in your GY; Set that target, but place it on the bottom of
+    the Deck when it leaves the field. You can only use this effect of "Malice, Lady
+    of Lament" once per turn.'
+  - Remove from play 1 "Assault Mode Activate" from your GY. Destroy all monsters
+    you control and Special Summon 1 "/Assault Mode" monster from your GY, ignoring
+    its Summoning conditions. Its effect(s) is negated, and it cannot be Tributed.
+    If it is removed from the field, remove it from play.
+datasets:
+- Tien09/pair_similarity_new_1
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# MPNet base trained on AllNLI triplets
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the [pair_similarity_new_1](https://huggingface.co/datasets/Tien09/pair_similarity_new_1) dataset. It maps sentences & paragraphs to a 128-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:** [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) <!-- at revision 6f75de8b60a9f8a2fdf7b69cbd86d9e64bcb3837 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 128 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Training Dataset:**
+    - [pair_similarity_new_1](https://huggingface.co/datasets/Tien09/pair_similarity_new_1)
+- **Language:** en
+- **License:** apache-2.0
+
+### 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}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 128, '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:
+
+```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("Tien09/tiny_bert_ft_sim_score_1")
+# Run inference
+sentences = [
+    '2 Cyberse monsters If this card is Link Summoned: You can add 1 "Cynet Fusion" from your Deck to your hand. If a monster(s) is Special Summoned to a zone(s) this card points to (except during the Damage Step): You can target 1 Level 4 or lower Cyberse monster in your GY; Special Summon it, but negate its effects, also you cannot Special Summon monsters from the Extra Deck for the rest of this turn, except Fusion Monsters. You can only use each effect of "Clock Spartoi" once per turn.',
+    'You can banish 1 "Virtual World" card from your GY, then target 1 face-up monster on the field; negate its effects until the end of this turn (even if this card leaves the field). You can banish this card from your GY; add 1 "Virtual World" monster from your Deck to your hand, then send 1 card from your hand to the GY. You can only use each effect of "Virtual World Gate - Qinglong" once per turn.',
+    'Remove from play 1 "Assault Mode Activate" from your GY. Destroy all monsters you control and Special Summon 1 "/Assault Mode" monster from your GY, ignoring its Summoning conditions. Its effect(s) is negated, and it cannot be Tributed. If it is removed from the field, remove it from play.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 128]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### 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.*
+-->
+
+<!--
+## 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
+
+#### pair_similarity_new_1
+
+* Dataset: [pair_similarity_new_1](https://huggingface.co/datasets/Tien09/pair_similarity_new_1) at [c49380e](https://huggingface.co/datasets/Tien09/pair_similarity_new_1/tree/c49380e225d024f12dda0a938f22ef44ca3168ba)
+* Size: 8,959 training samples
+* Columns: <code>effect_text</code>, <code>score</code>, and <code>effect_text2</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | effect_text                                                                        | score                                                          | effect_text2                                                                       |
+  |:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------|:-----------------------------------------------------------------------------------|
+  | type    | string                                                                             | float                                                          | string                                                                             |
+  | details | <ul><li>min: 9 tokens</li><li>mean: 73.57 tokens</li><li>max: 204 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.74</li><li>max: 1.0</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 73.05 tokens</li><li>max: 181 tokens</li></ul> |
+* Samples:
+  | effect_text                                                                                                                                                                       | score            | effect_text2                                                                                                                                                                                                                                                                                                 |
+  |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>When your opponent's monster attacks a face-up Level 4 or lower Toon Monster on your side of the field, you can make the attack a direct attack to your Life Points.</code> | <code>0.0</code> | <code>During either player's Main Phase: Special Summon this card as a Normal Monster (Reptile-Type/EARTH/Level 4/ATK 1600/DEF 1800). (This card is also still a Trap Card.)</code>                                                                                                                          |
+  | <code>When your opponent Special Summons a monster, you can discard 1 card to Special Summon this card from your hand. Your opponent cannot remove cards from play.</code>        | <code>1.0</code> | <code>Activate this card by discarding 1 monster, then target 1 monster in your GY whose Level is lower than the discarded monster's original Level; Special Summon it and equip it with this card. The equipped monster has its effects negated. You can only activate 1 "Overdone Burial" per turn.</code> |
+  | <code>Mystical Elf" + "Curtain of the Dark Ones</code>                                                                                                                            | <code>0.0</code> | <code>A destructive machine discovered in the Ruins of the Ancients.</code>                                                                                                                                                                                                                                  |
+* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "pairwise_cos_sim"
+  }
+  ```
+
+### Evaluation Dataset
+
+#### pair_similarity_new_1
+
+* Dataset: [pair_similarity_new_1](https://huggingface.co/datasets/Tien09/pair_similarity_new_1) at [c49380e](https://huggingface.co/datasets/Tien09/pair_similarity_new_1/tree/c49380e225d024f12dda0a938f22ef44ca3168ba)
+* Size: 1,920 evaluation samples
+* Columns: <code>effect_text</code>, <code>score</code>, and <code>effect_text2</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | effect_text                                                                        | score                                                          | effect_text2                                                                      |
+  |:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------|:----------------------------------------------------------------------------------|
+  | type    | string                                                                             | float                                                          | string                                                                            |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 72.29 tokens</li><li>max: 190 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.74</li><li>max: 1.0</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 72.2 tokens</li><li>max: 185 tokens</li></ul> |
+* Samples:
+  | effect_text                                                                                                                                                                                                                                                                                                                                                                                  | score            | effect_text2                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>2+ Level 4 monsters<br>This Xyz Summoned card gains 500 ATK x the total Link Rating of Link Monsters linked to this card. You can detach 2 materials from this card, then target 1 4 Cyberse Link Monster in your GY; Special Summon it to your field so it points to this card, also you cannot Special Summon other monsters or attack directly for the rest of this turn.</code>    | <code>1.0</code> | <code>3 Level 4 monsters Once per turn, you can also Xyz Summon "Zoodiac Tigermortar" by using 1 "Zoodiac" monster you control with a different name as Xyz Material. (If you used an Xyz Monster, any Xyz Materials attached to it also become Xyz Materials on this card.) This card gains ATK and DEF equal to the ATK and DEF of all "Zoodiac" monsters attached to it as Materials. Once per turn: You can detach 1 Xyz Material from this card, then target 1 Xyz Monster you control and 1 "Zoodiac" monster in your GY; attach that "Zoodiac" monster to that Xyz Monster as Xyz Material.</code> |
+  | <code>1 Tuner + 1 or more non-Tuner Pendulum Monsters Once per turn: You can target 1 Pendulum Monster on the field or 1 card in the Pendulum Zone; destroy it, and if you do, shuffle 1 card on the field into the Deck. Once per turn: You can Special Summon 1 "Dracoslayer" monster from your Deck in Defense Position, but it cannot be used as a Synchro Material for a Summon.</code> | <code>0.5</code> | <code>You can Ritual Summon this card with a "Recipe" card. If this card is Special Summoned: You can target 1 Spell/Trap on the field; destroy it. When a card or effect is activated that targets this card on the field, or when this card is targeted for an attack (Quick Effect): You can Tribute this card and 1 Attack Position monster on either field, and if you do, Special Summon 1 Level 3 or 4 "Nouvelles" Ritual Monster from your hand or Deck. You can only use each effect of "Confiras de Nouvelles" once per turn.</code>                                                            |
+  | <code>If you control an Illusion or Spellcaster monster: Add 1 "White Forest" monster from your Deck to your hand. If this card is sent to the GY to activate a monster effect: You can Set this card. You can only use each effect of "Tales of the White Forest" once per turn.</code>                                                                                                     | <code>1.0</code> | <code>If you control no monsters, you can Special Summon this card (from your hand). You can only use each of the following effects of "Kashtira Fenrir" once per turn. During your Main Phase: You can add 1 "Kashtira" monster from your Deck to your hand. When this card declares an attack, or if your opponent activates a monster effect (except during the Damage Step): You can target 1 face-up card your opponent controls; banish it, face-down.</code>                                                                                                                                       |
+* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "pairwise_cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `num_train_epochs`: 5
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `batch_sampler`: no_duplicates
+
+#### 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`: 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
+- `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`: 1.0
+- `num_train_epochs`: 5
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `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`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.1786 | 100  | 4.6579        | 4.3287          |
+| 0.3571 | 200  | 4.3378        | 4.2222          |
+| 0.5357 | 300  | 4.2299        | 4.1919          |
+| 0.7143 | 400  | 4.2124        | 4.1616          |
+| 0.8929 | 500  | 4.1399        | 4.1370          |
+| 1.0714 | 600  | 4.2017        | 4.1200          |
+| 1.25   | 700  | 4.1343        | 4.1058          |
+| 1.4286 | 800  | 4.0805        | 4.1072          |
+| 1.6071 | 900  | 4.0843        | 4.0773          |
+| 1.7857 | 1000 | 4.01          | 4.0771          |
+| 1.9643 | 1100 | 4.0615        | 4.0627          |
+| 2.1429 | 1200 | 4.0847        | 4.0468          |
+| 2.3214 | 1300 | 3.9798        | 4.0659          |
+| 2.5    | 1400 | 3.9663        | 4.0551          |
+| 2.6786 | 1500 | 3.9625        | 4.0335          |
+| 2.8571 | 1600 | 3.9096        | 4.0306          |
+| 3.0357 | 1700 | 4.0127        | 4.0105          |
+| 3.2143 | 1800 | 3.9753        | 4.0077          |
+| 3.3929 | 1900 | 3.8669        | 4.0188          |
+| 3.5714 | 2000 | 3.8983        | 4.0174          |
+| 3.75   | 2100 | 3.9077        | 4.0025          |
+| 3.9286 | 2200 | 3.8346        | 4.0218          |
+| 4.1071 | 2300 | 3.9618        | 3.9921          |
+| 4.2857 | 2400 | 3.8631        | 3.9981          |
+| 4.4643 | 2500 | 3.8456        | 4.0014          |
+| 4.6429 | 2600 | 3.8655        | 3.9976          |
+| 4.8214 | 2700 | 3.8248        | 4.0031          |
+| 5.0    | 2800 | 3.8935        | 4.0016          |
+
+
+### Framework Versions
+- Python: 3.10.12
+- Sentence Transformers: 3.3.1
+- Transformers: 4.47.1
+- PyTorch: 2.5.1+cu121
+- Accelerate: 1.2.1
+- Datasets: 3.2.0
+- 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",
+}
+```
+
+#### CoSENTLoss
+```bibtex
+@online{kexuefm-8847,
+    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
+    author={Su Jianlin},
+    year={2022},
+    month={Jan},
+    url={https://kexue.fm/archives/8847},
+}
+```
+
+<!--
+## 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 +1,25 @@
+{
+  "_name_or_path": "prajjwal1/bert-tiny",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 2,
+  "num_hidden_layers": 2,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.3.1",
+    "transformers": "4.47.1",
+    "pytorch": "2.5.1+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4257585363499b38eeb40118f60e0132c40870a7a2dbb360064f3633a966953c
+size 17547912

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

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

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,58 @@
+{
+  "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_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}