Add new SentenceTransformer model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+    "word_embedding_dimension": 1024,
+    "pooling_mode_cls_token": false,
+    "pooling_mode_mean_tokens": false,
+    "pooling_mode_max_tokens": false,
+    "pooling_mode_mean_sqrt_len_tokens": false,
+    "pooling_mode_weightedmean_tokens": false,
+    "pooling_mode_lasttoken": true,
+    "include_prompt": true
+}

README.md

@@ -0,0 +1,785 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:1310129
+- loss:MultipleNegativesRankingLoss
+base_model: unsloth/Qwen3-Embedding-0.6B
+widget:
+- source_sentence: 닥터브로너스 [페이셜&바디워시] 닥터브로너스 퓨어 캐스틸 솝 475ml 12종 택1
+  sentences:
+  - 露得清卸妆油
+  - Versace Man Eau Fraiche
+  - ピュアキャスティールソープ
+- source_sentence: 베르사체 베르사체 맨오프레쉬 30ml 단품/기획 택1
+  sentences:
+  - ピーリングジェル
+  - Versace Bright
+  - Man Eau Fraiche single
+- source_sentence: 랑방 랑방 루머 2 로즈 50ml
+  sentences:
+  - 캐스틸 솝 475ml
+  - 랑방 루머
+  - 防晒霜
+- source_sentence: 케어존 케어존 데일리&패밀리 선크림 80ml (SPF50+/PA+++)
+  sentences:
+  - 伊丽莎白雅顿 100毫升
+  - Rumeur Rose perfume
+  - 패밀리 선크림
+- source_sentence: 랑방 랑방 메리미 EDP 50ml
+  sentences:
+  - マリーミー EDP
+  - 浪凡 EDP
+  - ケアゾーン デイリー日焼け止め
+datasets:
+- dkqjrm/olive-product
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on unsloth/Qwen3-Embedding-0.6B
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [unsloth/Qwen3-Embedding-0.6B](https://huggingface.co/unsloth/Qwen3-Embedding-0.6B) on the [olive-product](https://huggingface.co/datasets/dkqjrm/olive-product) dataset. 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:** [unsloth/Qwen3-Embedding-0.6B](https://huggingface.co/unsloth/Qwen3-Embedding-0.6B) <!-- at revision f2fddb42505bde9feaf19f0967b01dce52e764c6 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 1024 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Training Dataset:**
+    - [olive-product](https://huggingface.co/datasets/dkqjrm/olive-product)
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/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': 'PeftModelForFeatureExtraction'})
+  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': True, '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("dkqjrm/lora_model")
+# Run inference
+sentences = [
+    '랑방 랑방 메리미 EDP 50ml',
+    '浪凡 EDP',
+    'マリーミー EDP',
+]
+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, 0.6852, 0.6339],
+#         [0.6852, 1.0000, 0.3744],
+#         [0.6339, 0.3744, 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.*
+-->
+
+<!--
+## 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
+
+#### olive-product
+
+* Dataset: [olive-product](https://huggingface.co/datasets/dkqjrm/olive-product) at [8d1f081](https://huggingface.co/datasets/dkqjrm/olive-product/tree/8d1f0813721299cb95f6d5cc09b2ef9317e8d06c)
+* Size: 1,310,129 training samples
+* Columns: <code>anchor</code> and <code>positive</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                             | positive                                                                         |
+  |:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|
+  | type    | string                                                                             | string                                                                           |
+  | details | <ul><li>min: 16 tokens</li><li>mean: 25.67 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 7.19 tokens</li><li>max: 38 tokens</li></ul> |
+* Samples:
+  | anchor                                   | positive                           |
+  |:-----------------------------------------|:-----------------------------------|
+  | <code>베르사체 베르사체 브라이트 크리스탈 50ml 택1</code> | <code>베르사체 브라이트 크리스탈 50ml 1</code> |
+  | <code>베르사체 베르사체 브라이트 크리스탈 50ml 택1</code> | <code>베르사체 브라이트</code>             |
+  | <code>베르사체 베르사체 브라이트 크리스탈 50ml 택1</code> | <code>베르사체 크리스탈</code>             |
+* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim",
+      "gather_across_devices": false
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 32
+- `gradient_accumulation_steps`: 4
+- `learning_rate`: 3e-05
+- `num_train_epochs`: 2
+- `lr_scheduler_type`: constant_with_warmup
+- `warmup_ratio`: 0.03
+- `fp16`: True
+- `push_to_hub`: True
+- `hub_model_id`: dkqjrm/qwen3-embedding-olive-lora
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: no
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 32
+- `per_device_eval_batch_size`: 8
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 4
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 3e-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`: 2
+- `max_steps`: -1
+- `lr_scheduler_type`: constant_with_warmup
+- `lr_scheduler_kwargs`: None
+- `warmup_ratio`: 0.03
+- `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
+- `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}
+- `parallelism_config`: None
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch_fused
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `project`: huggingface
+- `trackio_space_id`: trackio
+- `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`: True
+- `resume_from_checkpoint`: None
+- `hub_model_id`: dkqjrm/qwen3-embedding-olive-lora
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `hub_revision`: None
+- `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
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: no
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: True
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch  | Step  | Training Loss |
+|:------:|:-----:|:-------------:|
+| 0.0049 | 50    | 1.5027        |
+| 0.0098 | 100   | 0.8366        |
+| 0.0147 | 150   | 0.6713        |
+| 0.0195 | 200   | 0.5863        |
+| 0.0244 | 250   | 0.53          |
+| 0.0293 | 300   | 0.4562        |
+| 0.0342 | 350   | 0.4061        |
+| 0.0391 | 400   | 0.3899        |
+| 0.0440 | 450   | 0.3417        |
+| 0.0488 | 500   | 0.3367        |
+| 0.0537 | 550   | 0.2948        |
+| 0.0586 | 600   | 0.281         |
+| 0.0635 | 650   | 0.2808        |
+| 0.0684 | 700   | 0.2414        |
+| 0.0733 | 750   | 0.2448        |
+| 0.0782 | 800   | 0.2307        |
+| 0.0830 | 850   | 0.2174        |
+| 0.0879 | 900   | 0.2129        |
+| 0.0928 | 950   | 0.2139        |
+| 0.0977 | 1000  | 0.198         |
+| 0.1026 | 1050  | 0.1797        |
+| 0.1075 | 1100  | 0.1923        |
+| 0.1124 | 1150  | 0.1887        |
+| 0.1172 | 1200  | 0.1789        |
+| 0.1221 | 1250  | 0.1833        |
+| 0.1270 | 1300  | 0.168         |
+| 0.1319 | 1350  | 0.1683        |
+| 0.1368 | 1400  | 0.1536        |
+| 0.1417 | 1450  | 0.1632        |
+| 0.1465 | 1500  | 0.155         |
+| 0.1514 | 1550  | 0.1533        |
+| 0.1563 | 1600  | 0.1442        |
+| 0.1612 | 1650  | 0.1407        |
+| 0.1661 | 1700  | 0.1396        |
+| 0.1710 | 1750  | 0.1388        |
+| 0.1759 | 1800  | 0.1375        |
+| 0.1807 | 1850  | 0.1356        |
+| 0.1856 | 1900  | 0.1335        |
+| 0.1905 | 1950  | 0.1296        |
+| 0.1954 | 2000  | 0.1281        |
+| 0.2003 | 2050  | 0.1379        |
+| 0.2052 | 2100  | 0.1213        |
+| 0.2101 | 2150  | 0.1209        |
+| 0.2149 | 2200  | 0.1142        |
+| 0.2198 | 2250  | 0.1305        |
+| 0.2247 | 2300  | 0.115         |
+| 0.2296 | 2350  | 0.1125        |
+| 0.2345 | 2400  | 0.1159        |
+| 0.2394 | 2450  | 0.1131        |
+| 0.2442 | 2500  | 0.1133        |
+| 0.2491 | 2550  | 0.1126        |
+| 0.2540 | 2600  | 0.109         |
+| 0.2589 | 2650  | 0.1135        |
+| 0.2638 | 2700  | 0.0986        |
+| 0.2687 | 2750  | 0.1127        |
+| 0.2736 | 2800  | 0.114         |
+| 0.2784 | 2850  | 0.1079        |
+| 0.2833 | 2900  | 0.1106        |
+| 0.2882 | 2950  | 0.1112        |
+| 0.2931 | 3000  | 0.1006        |
+| 0.2980 | 3050  | 0.1051        |
+| 0.3029 | 3100  | 0.1105        |
+| 0.3078 | 3150  | 0.1046        |
+| 0.3126 | 3200  | 0.1011        |
+| 0.3175 | 3250  | 0.0962        |
+| 0.3224 | 3300  | 0.1002        |
+| 0.3273 | 3350  | 0.1066        |
+| 0.3322 | 3400  | 0.0907        |
+| 0.3371 | 3450  | 0.0894        |
+| 0.3419 | 3500  | 0.1002        |
+| 0.3468 | 3550  | 0.0894        |
+| 0.3517 | 3600  | 0.0897        |
+| 0.3566 | 3650  | 0.0995        |
+| 0.3615 | 3700  | 0.0949        |
+| 0.3664 | 3750  | 0.0914        |
+| 0.3713 | 3800  | 0.0929        |
+| 0.3761 | 3850  | 0.0841        |
+| 0.3810 | 3900  | 0.0847        |
+| 0.3859 | 3950  | 0.0964        |
+| 0.3908 | 4000  | 0.0937        |
+| 0.3957 | 4050  | 0.0874        |
+| 0.4006 | 4100  | 0.0911        |
+| 0.4055 | 4150  | 0.093         |
+| 0.4103 | 4200  | 0.0867        |
+| 0.4152 | 4250  | 0.0841        |
+| 0.4201 | 4300  | 0.083         |
+| 0.4250 | 4350  | 0.0908        |
+| 0.4299 | 4400  | 0.0829        |
+| 0.4348 | 4450  | 0.0871        |
+| 0.4396 | 4500  | 0.0799        |
+| 0.4445 | 4550  | 0.0777        |
+| 0.4494 | 4600  | 0.0873        |
+| 0.4543 | 4650  | 0.0805        |
+| 0.4592 | 4700  | 0.0851        |
+| 0.4641 | 4750  | 0.0855        |
+| 0.4690 | 4800  | 0.0763        |
+| 0.4738 | 4850  | 0.082         |
+| 0.4787 | 4900  | 0.0699        |
+| 0.4836 | 4950  | 0.0802        |
+| 0.4885 | 5000  | 0.0807        |
+| 0.4934 | 5050  | 0.0746        |
+| 0.4983 | 5100  | 0.0705        |
+| 0.5032 | 5150  | 0.0707        |
+| 0.5080 | 5200  | 0.0827        |
+| 0.5129 | 5250  | 0.0808        |
+| 0.5178 | 5300  | 0.0835        |
+| 0.5227 | 5350  | 0.0782        |
+| 0.5276 | 5400  | 0.0698        |
+| 0.5325 | 5450  | 0.0755        |
+| 0.5373 | 5500  | 0.0743        |
+| 0.5422 | 5550  | 0.0744        |
+| 0.5471 | 5600  | 0.0724        |
+| 0.5520 | 5650  | 0.0781        |
+| 0.5569 | 5700  | 0.0712        |
+| 0.5618 | 5750  | 0.0738        |
+| 0.5667 | 5800  | 0.0692        |
+| 0.5715 | 5850  | 0.0747        |
+| 0.5764 | 5900  | 0.0686        |
+| 0.5813 | 5950  | 0.0761        |
+| 0.5862 | 6000  | 0.0696        |
+| 0.5911 | 6050  | 0.0681        |
+| 0.5960 | 6100  | 0.0714        |
+| 0.6008 | 6150  | 0.0682        |
+| 0.6057 | 6200  | 0.0746        |
+| 0.6106 | 6250  | 0.0638        |
+| 0.6155 | 6300  | 0.0672        |
+| 0.6204 | 6350  | 0.0727        |
+| 0.6253 | 6400  | 0.0711        |
+| 0.6302 | 6450  | 0.0716        |
+| 0.6350 | 6500  | 0.0609        |
+| 0.6399 | 6550  | 0.066         |
+| 0.6448 | 6600  | 0.0709        |
+| 0.6497 | 6650  | 0.0687        |
+| 0.6546 | 6700  | 0.0629        |
+| 0.6595 | 6750  | 0.0693        |
+| 0.6644 | 6800  | 0.0678        |
+| 0.6692 | 6850  | 0.0612        |
+| 0.6741 | 6900  | 0.0653        |
+| 0.6790 | 6950  | 0.0642        |
+| 0.6839 | 7000  | 0.068         |
+| 0.6888 | 7050  | 0.0626        |
+| 0.6937 | 7100  | 0.0623        |
+| 0.6985 | 7150  | 0.0622        |
+| 0.7034 | 7200  | 0.0661        |
+| 0.7083 | 7250  | 0.0597        |
+| 0.7132 | 7300  | 0.0584        |
+| 0.7181 | 7350  | 0.0595        |
+| 0.7230 | 7400  | 0.0647        |
+| 0.7279 | 7450  | 0.0664        |
+| 0.7327 | 7500  | 0.0682        |
+| 0.7376 | 7550  | 0.0621        |
+| 0.7425 | 7600  | 0.0603        |
+| 0.7474 | 7650  | 0.0617        |
+| 0.7523 | 7700  | 0.0554        |
+| 0.7572 | 7750  | 0.056         |
+| 0.7621 | 7800  | 0.0594        |
+| 0.7669 | 7850  | 0.0594        |
+| 0.7718 | 7900  | 0.0618        |
+| 0.7767 | 7950  | 0.0638        |
+| 0.7816 | 8000  | 0.0556        |
+| 0.7865 | 8050  | 0.0608        |
+| 0.7914 | 8100  | 0.0624        |
+| 0.7962 | 8150  | 0.0621        |
+| 0.8011 | 8200  | 0.0653        |
+| 0.8060 | 8250  | 0.0648        |
+| 0.8109 | 8300  | 0.0533        |
+| 0.8158 | 8350  | 0.0584        |
+| 0.8207 | 8400  | 0.0552        |
+| 0.8256 | 8450  | 0.066         |
+| 0.8304 | 8500  | 0.0616        |
+| 0.8353 | 8550  | 0.0648        |
+| 0.8402 | 8600  | 0.0618        |
+| 0.8451 | 8650  | 0.0587        |
+| 0.8500 | 8700  | 0.0616        |
+| 0.8549 | 8750  | 0.0544        |
+| 0.8598 | 8800  | 0.0637        |
+| 0.8646 | 8850  | 0.0621        |
+| 0.8695 | 8900  | 0.0574        |
+| 0.8744 | 8950  | 0.0587        |
+| 0.8793 | 9000  | 0.0606        |
+| 0.8842 | 9050  | 0.0595        |
+| 0.8891 | 9100  | 0.0627        |
+| 0.8939 | 9150  | 0.0564        |
+| 0.8988 | 9200  | 0.0542        |
+| 0.9037 | 9250  | 0.0538        |
+| 0.9086 | 9300  | 0.055         |
+| 0.9135 | 9350  | 0.0562        |
+| 0.9184 | 9400  | 0.0547        |
+| 0.9233 | 9450  | 0.0514        |
+| 0.9281 | 9500  | 0.0574        |
+| 0.9330 | 9550  | 0.0503        |
+| 0.9379 | 9600  | 0.0647        |
+| 0.9428 | 9650  | 0.0554        |
+| 0.9477 | 9700  | 0.0532        |
+| 0.9526 | 9750  | 0.056         |
+| 0.9575 | 9800  | 0.0554        |
+| 0.9623 | 9850  | 0.0535        |
+| 0.9672 | 9900  | 0.0553        |
+| 0.9721 | 9950  | 0.0581        |
+| 0.9770 | 10000 | 0.05          |
+| 0.9819 | 10050 | 0.0571        |
+| 0.9868 | 10100 | 0.0534        |
+| 0.9916 | 10150 | 0.0462        |
+| 0.9965 | 10200 | 0.0508        |
+| 1.0014 | 10250 | 0.0506        |
+| 1.0063 | 10300 | 0.0548        |
+| 1.0111 | 10350 | 0.0476        |
+| 1.0160 | 10400 | 0.0504        |
+| 1.0209 | 10450 | 0.0433        |
+| 1.0258 | 10500 | 0.0499        |
+| 1.0307 | 10550 | 0.0453        |
+| 1.0356 | 10600 | 0.0494        |
+| 1.0404 | 10650 | 0.0456        |
+| 1.0453 | 10700 | 0.0499        |
+| 1.0502 | 10750 | 0.049         |
+| 1.0551 | 10800 | 0.0464        |
+| 1.0600 | 10850 | 0.0483        |
+| 1.0649 | 10900 | 0.0487        |
+| 1.0698 | 10950 | 0.0461        |
+| 1.0746 | 11000 | 0.0433        |
+| 1.0795 | 11050 | 0.0474        |
+| 1.0844 | 11100 | 0.0485        |
+| 1.0893 | 11150 | 0.0462        |
+| 1.0942 | 11200 | 0.0396        |
+| 1.0991 | 11250 | 0.0479        |
+| 1.1040 | 11300 | 0.0471        |
+| 1.1088 | 11350 | 0.0473        |
+| 1.1137 | 11400 | 0.0482        |
+| 1.1186 | 11450 | 0.0412        |
+| 1.1235 | 11500 | 0.0455        |
+| 1.1284 | 11550 | 0.0448        |
+| 1.1333 | 11600 | 0.0531        |
+| 1.1381 | 11650 | 0.0466        |
+| 1.1430 | 11700 | 0.0527        |
+| 1.1479 | 11750 | 0.0465        |
+| 1.1528 | 11800 | 0.0536        |
+| 1.1577 | 11850 | 0.0474        |
+| 1.1626 | 11900 | 0.0515        |
+| 1.1675 | 11950 | 0.0429        |
+| 1.1723 | 12000 | 0.0464        |
+| 1.1772 | 12050 | 0.0463        |
+| 1.1821 | 12100 | 0.0491        |
+| 1.1870 | 12150 | 0.0433        |
+| 1.1919 | 12200 | 0.0466        |
+| 1.1968 | 12250 | 0.0522        |
+| 1.2017 | 12300 | 0.0463        |
+| 1.2065 | 12350 | 0.0528        |
+| 1.2114 | 12400 | 0.0451        |
+| 1.2163 | 12450 | 0.0449        |
+| 1.2212 | 12500 | 0.0475        |
+| 1.2261 | 12550 | 0.0468        |
+| 1.2310 | 12600 | 0.0456        |
+| 1.2358 | 12650 | 0.0411        |
+| 1.2407 | 12700 | 0.0439        |
+| 1.2456 | 12750 | 0.0434        |
+| 1.2505 | 12800 | 0.0475        |
+| 1.2554 | 12850 | 0.0468        |
+| 1.2603 | 12900 | 0.046         |
+| 1.2652 | 12950 | 0.0467        |
+| 1.2700 | 13000 | 0.0429        |
+| 1.2749 | 13050 | 0.0437        |
+| 1.2798 | 13100 | 0.048         |
+| 1.2847 | 13150 | 0.0429        |
+| 1.2896 | 13200 | 0.0507        |
+| 1.2945 | 13250 | 0.0426        |
+| 1.2994 | 13300 | 0.0408        |
+| 1.3042 | 13350 | 0.0468        |
+| 1.3091 | 13400 | 0.0389        |
+| 1.3140 | 13450 | 0.0458        |
+| 1.3189 | 13500 | 0.044         |
+| 1.3238 | 13550 | 0.0417        |
+| 1.3287 | 13600 | 0.0437        |
+| 1.3335 | 13650 | 0.0427        |
+| 1.3384 | 13700 | 0.0444        |
+| 1.3433 | 13750 | 0.0496        |
+| 1.3482 | 13800 | 0.0443        |
+| 1.3531 | 13850 | 0.0421        |
+| 1.3580 | 13900 | 0.0431        |
+| 1.3629 | 13950 | 0.0474        |
+| 1.3677 | 14000 | 0.0423        |
+| 1.3726 | 14050 | 0.0437        |
+| 1.3775 | 14100 | 0.038         |
+| 1.3824 | 14150 | 0.0457        |
+| 1.3873 | 14200 | 0.0459        |
+| 1.3922 | 14250 | 0.0421        |
+| 1.3970 | 14300 | 0.0482        |
+| 1.4019 | 14350 | 0.0496        |
+| 1.4068 | 14400 | 0.0436        |
+| 1.4117 | 14450 | 0.0437        |
+| 1.4166 | 14500 | 0.0463        |
+| 1.4215 | 14550 | 0.04          |
+| 1.4264 | 14600 | 0.046         |
+| 1.4312 | 14650 | 0.0451        |
+| 1.4361 | 14700 | 0.044         |
+| 1.4410 | 14750 | 0.0436        |
+| 1.4459 | 14800 | 0.0411        |
+| 1.4508 | 14850 | 0.0453        |
+| 1.4557 | 14900 | 0.0402        |
+| 1.4606 | 14950 | 0.0437        |
+| 1.4654 | 15000 | 0.0451        |
+| 1.4703 | 15050 | 0.0454        |
+| 1.4752 | 15100 | 0.0433        |
+| 1.4801 | 15150 | 0.0399        |
+| 1.4850 | 15200 | 0.0389        |
+| 1.4899 | 15250 | 0.0451        |
+| 1.4947 | 15300 | 0.0417        |
+| 1.4996 | 15350 | 0.0411        |
+| 1.5045 | 15400 | 0.0415        |
+| 1.5094 | 15450 | 0.044         |
+| 1.5143 | 15500 | 0.045         |
+| 1.5192 | 15550 | 0.0414        |
+| 1.5241 | 15600 | 0.0439        |
+| 1.5289 | 15650 | 0.0381        |
+| 1.5338 | 15700 | 0.0425        |
+| 1.5387 | 15750 | 0.0439        |
+| 1.5436 | 15800 | 0.0405        |
+| 1.5485 | 15850 | 0.0407        |
+| 1.5534 | 15900 | 0.04          |
+| 1.5583 | 15950 | 0.0404        |
+| 1.5631 | 16000 | 0.0392        |
+| 1.5680 | 16050 | 0.0432        |
+| 1.5729 | 16100 | 0.0374        |
+| 1.5778 | 16150 | 0.044         |
+| 1.5827 | 16200 | 0.0429        |
+| 1.5876 | 16250 | 0.0394        |
+| 1.5924 | 16300 | 0.0446        |
+| 1.5973 | 16350 | 0.0389        |
+| 1.6022 | 16400 | 0.0429        |
+| 1.6071 | 16450 | 0.0442        |
+| 1.6120 | 16500 | 0.0394        |
+| 1.6169 | 16550 | 0.0403        |
+| 1.6218 | 16600 | 0.0414        |
+| 1.6266 | 16650 | 0.0386        |
+| 1.6315 | 16700 | 0.0401        |
+| 1.6364 | 16750 | 0.0415        |
+| 1.6413 | 16800 | 0.0427        |
+| 1.6462 | 16850 | 0.0412        |
+| 1.6511 | 16900 | 0.0404        |
+| 1.6560 | 16950 | 0.0402        |
+| 1.6608 | 17000 | 0.0394        |
+| 1.6657 | 17050 | 0.0429        |
+| 1.6706 | 17100 | 0.0452        |
+| 1.6755 | 17150 | 0.0438        |
+| 1.6804 | 17200 | 0.0433        |
+| 1.6853 | 17250 | 0.0393        |
+| 1.6901 | 17300 | 0.0405        |
+| 1.6950 | 17350 | 0.044         |
+| 1.6999 | 17400 | 0.042         |
+| 1.7048 | 17450 | 0.0401        |
+| 1.7097 | 17500 | 0.0417        |
+| 1.7146 | 17550 | 0.0351        |
+| 1.7195 | 17600 | 0.0367        |
+| 1.7243 | 17650 | 0.0436        |
+| 1.7292 | 17700 | 0.0392        |
+| 1.7341 | 17750 | 0.04          |
+| 1.7390 | 17800 | 0.0415        |
+| 1.7439 | 17850 | 0.0418        |
+| 1.7488 | 17900 | 0.0366        |
+| 1.7537 | 17950 | 0.0433        |
+| 1.7585 | 18000 | 0.0391        |
+| 1.7634 | 18050 | 0.0377        |
+| 1.7683 | 18100 | 0.0398        |
+| 1.7732 | 18150 | 0.0396        |
+| 1.7781 | 18200 | 0.0404        |
+| 1.7830 | 18250 | 0.0405        |
+| 1.7878 | 18300 | 0.0381        |
+| 1.7927 | 18350 | 0.04          |
+| 1.7976 | 18400 | 0.0404        |
+| 1.8025 | 18450 | 0.0348        |
+| 1.8074 | 18500 | 0.0397        |
+| 1.8123 | 18550 | 0.042         |
+| 1.8172 | 18600 | 0.0454        |
+| 1.8220 | 18650 | 0.0384        |
+| 1.8269 | 18700 | 0.0387        |
+| 1.8318 | 18750 | 0.042         |
+| 1.8367 | 18800 | 0.0413        |
+| 1.8416 | 18850 | 0.0403        |
+| 1.8465 | 18900 | 0.0417        |
+| 1.8514 | 18950 | 0.0386        |
+| 1.8562 | 19000 | 0.0417        |
+| 1.8611 | 19050 | 0.0396        |
+| 1.8660 | 19100 | 0.039         |
+| 1.8709 | 19150 | 0.0403        |
+| 1.8758 | 19200 | 0.0402        |
+| 1.8807 | 19250 | 0.044         |
+| 1.8855 | 19300 | 0.0413        |
+| 1.8904 | 19350 | 0.0379        |
+| 1.8953 | 19400 | 0.042         |
+| 1.9002 | 19450 | 0.0389        |
+| 1.9051 | 19500 | 0.0399        |
+| 1.9100 | 19550 | 0.0405        |
+| 1.9149 | 19600 | 0.0414        |
+| 1.9197 | 19650 | 0.0406        |
+| 1.9246 | 19700 | 0.037         |
+| 1.9295 | 19750 | 0.0406        |
+| 1.9344 | 19800 | 0.0433        |
+| 1.9393 | 19850 | 0.0357        |
+| 1.9442 | 19900 | 0.038         |
+| 1.9490 | 19950 | 0.0444        |
+| 1.9539 | 20000 | 0.0406        |
+| 1.9588 | 20050 | 0.0343        |
+| 1.9637 | 20100 | 0.0414        |
+| 1.9686 | 20150 | 0.0359        |
+| 1.9735 | 20200 | 0.0421        |
+| 1.9784 | 20250 | 0.0352        |
+| 1.9832 | 20300 | 0.0406        |
+| 1.9881 | 20350 | 0.0403        |
+| 1.9930 | 20400 | 0.0396        |
+| 1.9979 | 20450 | 0.0378        |
+
+</details>
+
+### Framework Versions
+- Python: 3.12.12
+- Sentence Transformers: 5.2.1
+- Transformers: 4.57.6
+- PyTorch: 2.10.0+cu128
+- Accelerate: 1.12.0
+- Datasets: 4.3.0
+- Tokenizers: 0.22.2
+
+## 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",
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply},
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## 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.*
+-->

adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3Model",
+    "parent_library": "transformers.models.qwen3.modeling_qwen3",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/Qwen3-Embedding-0.6B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_proj",
+    "o_proj",
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "up_proj",
+    "down_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "FEATURE_EXTRACTION",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e36c44d6a67b847867b4fe98a805aebbb4e65aed84a8e98fbe9de930d710eacd
+size 161530808

added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

@@ -0,0 +1,85 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set content = message.content %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in message.content %}
+                {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
+                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.2.1",
+    "transformers": "4.57.6",
+    "pytorch": "2.10.0+cu128"
+  },
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

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 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a5b90ffcbd8fe896c9ee9fe56c5dd84116f876ad5cdbe0d1424fbe150f41ca6
+size 11423970

tokenizer_config.json

@@ -0,0 +1,240 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
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