Add new SentenceTransformer model

1_Pooling/config.json

@@ -1,5 +1,5 @@
 {
-    "word_embedding_dimension": 1024,
+    "word_embedding_dimension": 384,
     "pooling_mode_cls_token": false,
     "pooling_mode_mean_tokens": true,
     "pooling_mode_max_tokens": false,

README.md

@@ -12,51 +12,53 @@ tags:
 - retrieval
 - reranking
 - generated_from_trainer
-- dataset_size:9233417
+- dataset_size:13667
 - loss:ArcFaceInBatchLoss
-base_model: answerdotai/ModernBERT-large
+base_model: sentence-transformers/all-MiniLM-L6-v2
 widget:
-- source_sentence: Hayley Vaughan portrayed Ripa on the ABC daytime soap opera , ``
-    All My Children `` , between 1990 and 2002 .
+- source_sentence: It was mobilized in December 2014 from elements of the dissolved
+    51st Mechanized Brigade and newly formed units .
   sentences:
-  - Traxxpad is a music application for Sony 's PlayStation Portable published by
-    Definitive Studios and developed by Eidos Interactive .
-  - Between 1990 and 2002 , Hayley Vaughan Ripa portrayed in the ABC soap opera ``
-    All My Children `` .
-  - Between 1990 and 2002 , Ripa Hayley portrayed Vaughan in the ABC soap opera ``
-    All My Children `` .
-- source_sentence: Olivella monilifera is a species of dwarf sea snail , small gastropod
-    mollusk in the family Olivellidae , the marine olives .
+  - This North-South route falls entirely in the Belgian territory and runs together
+    with the Belgian roads N31 and A17 .
+  - It was mobilized in December 2014 from elements of the disbanded 51st Mechanized
+    Brigade and newly formed units .
+  - All windows are double wood , hung up with a single light .
+- source_sentence: It is located at Ellison Bay , in the town of Liberty Grove , Wisconsin
+    .
   sentences:
-  - Olivella monilifera is a species of the dwarf - sea snail , small gastropod mollusk
-    in the Olivellidae family , the marine olives .
-  - He was cut by the Browns after being signed by the Bills in 2013 . He was later
-    released .
-  - Olivella monilifera is a kind of sea snail , marine gastropod mollusk in the Olivellidae
-    family , the dwarf olives .
-- source_sentence: Hayashi said that Mackey `` is a sort of `` of the original model
-    for Tenchi .
+  - It is located in Ellison Bay , in the town of Liberty Grove , Wisconsin .
+  - It is located in Liberty Grove , Wisconsin , in the town of Ellison Bay .
+  - 'The Hadejia River ( Hausa : `` kogin Haɗeja `` ) is a river in northern Nigeria
+    and is a tributary of the Yobe River ( Komadugu Yobe ) .'
+- source_sentence: Both long and short vowels can be nasalized ( differentiation between
+    `` acces `` and `` Ä cces `` below ) , but long nasal vowels are more common .
   sentences:
-  - In the summer of 2009 , Ellick shot a documentary about Malala Yousafzai .
-  - Hayashi said that Mackey is `` sort of `` the original model for Tenchi .
-  - Mackey said that Hayashi is `` sort of `` the original model for Tenchi .
-- source_sentence: Much of the film was shot on location in Los Angeles and in nearby
-    Burbank and Glendale .
+  - Both long and short vowels can be nasalized ( the distinction between `` acces
+    `` and `` ącces `` below ) , but long nasal vowels are more common .
+  - Wilson was a member of the Senate from 1844 to 1846 and 1850 to 1852 . From 1851
+    to 1852 he was the Massachusetts State Senate 's President .
+  - Both long vowels can be nasalized ( the distinction between `` acces `` and ``
+    ącces `` below ) , but long and short nasal vowels are more common .
+- source_sentence: At that time , on June 22 , 1754 , Edward Bentham married Bentham
+    Elizabeth Bates ( d . 1790 ) from Hampshire in the nearby county of Alton .
   sentences:
-  - Much of the film was shot on location in Los Angeles and in nearby Burbank and
-    Glendale .
-  - Much of the film was shot on site in Burbank and Glendale and in the nearby Los
-    Angeles .
-  - Traxxpad is a music application for the Sony PlayStation Portable developed by
-    the Definitive Studios and published by Eidos Interactive .
-- source_sentence: According to him , the earth is the carrier of his artistic work
-    , which is only integrated into the creative process by minimal changes .
+  - The Department of Criminal Justice developed the first certificate program in
+    forensic science in North Carolina and sponsors a summer comparative studies program
+    based in Europe .
+  - At that time , on June 22 , 1754 , Edward Bentham married Bentham Elizabeth Bates
+    ( d . 1790 ) from Hampshire in the nearby county of Alton .
+  - It was at this time , on 22 June 1754 , that Edward Bentham married Elizabeth
+    Bates ( d 1790 ) from Alton in the nearby county of Hampshire .
+- source_sentence: In 1973 Michels ' apos broke ; Barcelona the world transfer record
+    to bring Cruyff to Catalonia .
   sentences:
-  - National players are Bold players .
-  - According to him , earth is the carrier of his artistic work being integrated
-    into the creative process only by minimal changes .
-  - According to him , earth is the carrier of his creative work being integrated
-    into the artistic process only by minimal changes .
+  - In 1973 , Cruyff 'Barcelona broke the world transfer record to bring Michels to
+    Catalonia .
+  - Amalric then marched to Cairo , where Shawar offered Amalric two million pieces
+    of gold .
+  - In 1973 Michels ' apos broke ; Barcelona the world transfer record to bring Cruyff
+    to Catalonia .
 datasets:
 - redis/langcache-sentencepairs-v2
 pipeline_tag: sentence-similarity
@@ -81,42 +83,42 @@ model-index:
       type: test
     metrics:
     - type: cosine_accuracy@1
-      value: 0.6070776173931731
+      value: 0.5763458576596583
       name: Cosine Accuracy@1
     - type: cosine_precision@1
-      value: 0.6070776173931731
+      value: 0.5763458576596583
       name: Cosine Precision@1
     - type: cosine_recall@1
-      value: 0.588632794022045
+      value: 0.5583264629675676
       name: Cosine Recall@1
     - type: cosine_ndcg@10
-      value: 0.7755359823507149
+      value: 0.7650954794467948
       name: Cosine Ndcg@10
     - type: cosine_mrr@1
-      value: 0.6070776173931731
+      value: 0.5763458576596583
       name: Cosine Mrr@1
     - type: cosine_map@100
-      value: 0.7291245351244533
+      value: 0.7127722828012101
       name: Cosine Map@100
     - type: cosine_auc_precision_cache_hit_ratio
-      value: 0.348058858138603
+      value: 0.333338757469584
       name: Cosine Auc Precision Cache Hit Ratio
     - type: cosine_auc_similarity_distribution
-      value: 0.21125989323367672
+      value: 0.1528271968812688
       name: Cosine Auc Similarity Distribution
 ---
 
 # Redis fine-tuned BiEncoder model for semantic caching on LangCache
 
-This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) dataset. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for sentence pair similarity.
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) dataset. It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for sentence pair similarity.
 
 ## Model Details
 
 ### Model Description
 - **Model Type:** Sentence Transformer
-- **Base model:** [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) <!-- at revision 45bb4654a4d5aaff24dd11d4781fa46d39bf8c13 -->
+- **Base model:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) <!-- at revision c9745ed1d9f207416be6d2e6f8de32d1f16199bf -->
 - **Maximum Sequence Length:** 100 tokens
-- **Output Dimensionality:** 1024 dimensions
+- **Output Dimensionality:** 384 dimensions
 - **Similarity Function:** Cosine Similarity
 - **Training Dataset:**
     - [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
@@ -133,8 +135,9 @@ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [a
 
 ```
 SentenceTransformer(
-  (0): Transformer({'max_seq_length': 100, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
-  (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})
+  (0): Transformer({'max_seq_length': 100, 'do_lower_case': False, 'architecture': 'BertModel'})
+  (1): Pooling({'word_embedding_dimension': 384, '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()
 )
 ```
 
@@ -156,20 +159,20 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer("redis/langcache-embed-experimental")
 # Run inference
 sentences = [
-    'According to him , the earth is the carrier of his artistic work , which is only integrated into the creative process by minimal changes .',
-    'According to him , earth is the carrier of his artistic work being integrated into the creative process only by minimal changes .',
-    'According to him , earth is the carrier of his creative work being integrated into the artistic process only by minimal changes .',
+    "In 1973 Michels ' apos broke ; Barcelona the world transfer record to bring Cruyff to Catalonia .",
+    "In 1973 Michels ' apos broke ; Barcelona the world transfer record to bring Cruyff to Catalonia .",
+    "In 1973 , Cruyff 'Barcelona broke the world transfer record to bring Michels to Catalonia .",
 ]
 embeddings = model.encode(sentences)
 print(embeddings.shape)
-# [3, 1024]
+# [3, 384]
 
 # Get the similarity scores for the embeddings
 similarities = model.similarity(embeddings, embeddings)
 print(similarities)
-# tensor([[1.0000, 0.9609, 0.4414],
-#         [0.9609, 1.0000, 0.4395],
-#         [0.4414, 0.4395, 1.0000]], dtype=torch.bfloat16)
+# tensor([[1.0000, 1.0000, 0.9219],
+#         [1.0000, 1.0000, 0.9219],
+#         [0.9219, 0.9219, 1.0078]], dtype=torch.bfloat16)
 ```
 
 <!--
@@ -207,14 +210,14 @@ You can finetune this model on your own dataset.
 
 | Metric                               | Value      |
 |:-------------------------------------|:-----------|
-| cosine_accuracy@1                    | 0.6071     |
-| cosine_precision@1                   | 0.6071     |
-| cosine_recall@1                      | 0.5886     |
-| **cosine_ndcg@10**                   | **0.7755** |
-| cosine_mrr@1                         | 0.6071     |
-| cosine_map@100                       | 0.7291     |
-| cosine_auc_precision_cache_hit_ratio | 0.3481     |
-| cosine_auc_similarity_distribution   | 0.2113     |
+| cosine_accuracy@1                    | 0.5763     |
+| cosine_precision@1                   | 0.5763     |
+| cosine_recall@1                      | 0.5583     |
+| **cosine_ndcg@10**                   | **0.7651** |
+| cosine_mrr@1                         | 0.5763     |
+| cosine_map@100                       | 0.7128     |
+| cosine_auc_precision_cache_hit_ratio | 0.3333     |
+| cosine_auc_similarity_distribution   | 0.1528     |
 
 <!--
 ## Bias, Risks and Limitations
@@ -235,18 +238,18 @@ You can finetune this model on your own dataset.
 #### LangCache Sentence Pairs (all)
 
 * Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
-* Size: 126,938 training samples
+* Size: 6,780 training samples
 * Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
 * Approximate statistics based on the first 1000 samples:
   |         | anchor                                                                            | positive                                                                          | negative                                                                          |
   |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
   | type    | string                                                                            | string                                                                            | string                                                                            |
-  | details | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 26.54 tokens</li><li>max: 61 tokens</li></ul> |
+  | details | <ul><li>min: 8 tokens</li><li>mean: 26.28 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 26.27 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 26.25 tokens</li><li>max: 47 tokens</li></ul> |
 * Samples:
   | anchor                                                                                                                                      | positive                                                                                                                                      | negative                                                                                                                                      |
   |:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
-  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>how can I get financial freedom as soon as possible?</code>                                                                             |
-  | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                         | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                          | <code>The older Punts are still very much in existence today and race in the same fleets as the newer boats .</code>                          |
+  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>This marine species occurs in the eastern Indian Ocean and before the Maldives and New Caledonia .</code>                               |
+  | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                         | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                          | <code>Both young people burn with love really , for both , but without being able to say it to himself , admitting him always .</code>        |
   | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley , , was located at Turner Valley Bar N Ranch Airport , southwest of Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> |
 * Loss: <code>losses.ArcFaceInBatchLoss</code> with these parameters:
   ```json
@@ -262,18 +265,18 @@ You can finetune this model on your own dataset.
 #### LangCache Sentence Pairs (all)
 
 * Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
-* Size: 126,938 evaluation samples
+* Size: 6,780 evaluation samples
 * Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
 * Approximate statistics based on the first 1000 samples:
   |         | anchor                                                                            | positive                                                                          | negative                                                                          |
   |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
   | type    | string                                                                            | string                                                                            | string                                                                            |
-  | details | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 26.54 tokens</li><li>max: 61 tokens</li></ul> |
+  | details | <ul><li>min: 8 tokens</li><li>mean: 26.28 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 26.27 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 26.25 tokens</li><li>max: 47 tokens</li></ul> |
 * Samples:
   | anchor                                                                                                                                      | positive                                                                                                                                      | negative                                                                                                                                      |
   |:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
-  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>how can I get financial freedom as soon as possible?</code>                                                                             |
-  | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                         | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                          | <code>The older Punts are still very much in existence today and race in the same fleets as the newer boats .</code>                          |
+  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>This marine species occurs in the eastern Indian Ocean and before the Maldives and New Caledonia .</code>                               |
+  | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                         | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                          | <code>Both young people burn with love really , for both , but without being able to say it to himself , admitting him always .</code>        |
   | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley , , was located at Turner Valley Bar N Ranch Airport , southwest of Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> |
 * Loss: <code>losses.ArcFaceInBatchLoss</code> with these parameters:
   ```json
@@ -284,307 +287,11 @@ You can finetune this model on your own dataset.
   }
   ```
 
-### Training Hyperparameters
-#### Non-Default Hyperparameters
-
-- `eval_strategy`: steps
-- `per_device_train_batch_size`: 100
-- `per_device_eval_batch_size`: 100
-- `weight_decay`: 0.001
-- `adam_beta2`: 0.98
-- `adam_epsilon`: 1e-06
-- `max_steps`: 75000
-- `warmup_ratio`: 0.1
-- `load_best_model_at_end`: True
-- `optim`: stable_adamw
-- `ddp_find_unused_parameters`: False
-- `push_to_hub`: True
-- `hub_model_id`: redis/langcache-embed-experimental
-- `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`: 100
-- `per_device_eval_batch_size`: 100
-- `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`: 0.001
-- `adam_beta1`: 0.9
-- `adam_beta2`: 0.98
-- `adam_epsilon`: 1e-06
-- `max_grad_norm`: 1.0
-- `num_train_epochs`: 3.0
-- `max_steps`: 75000
-- `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`: False
-- `fp16_opt_level`: O1
-- `half_precision_backend`: auto
-- `bf16_full_eval`: False
-- `fp16_full_eval`: False
-- `tf32`: None
-- `local_rank`: 0
-- `ddp_backend`: None
-- `tpu_num_cores`: None
-- `tpu_metrics_debug`: False
-- `debug`: []
-- `dataloader_drop_last`: False
-- `dataloader_num_workers`: 0
-- `dataloader_prefetch_factor`: None
-- `past_index`: -1
-- `disable_tqdm`: False
-- `remove_unused_columns`: True
-- `label_names`: None
-- `load_best_model_at_end`: True
-- `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`: stable_adamw
-- `optim_args`: None
-- `adafactor`: False
-- `group_by_length`: False
-- `length_column_name`: length
-- `ddp_find_unused_parameters`: False
-- `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`: redis/langcache-embed-experimental
-- `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`: False
-- `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`: False
-- `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 | test_cosine_ndcg@10 |
+|:-----:|:----:|:-------------------:|
+| -1    | -1   | 0.7651              |
 
-| Epoch      | Step      | Training Loss | Validation Loss | test_cosine_ndcg@10 |
-|:----------:|:---------:|:-------------:|:---------------:|:-------------------:|
-| -1         | -1        | -             | -               | 0.6274              |
-| 0.0054     | 500       | 2.0433        | 0.5003          | 0.7156              |
-| 0.0108     | 1000      | 0.2913        | 0.3804          | 0.7423              |
-| 0.0162     | 1500      | 0.1876        | 0.3343          | 0.7526              |
-| 0.0217     | 2000      | 0.1484        | 0.3172          | 0.7528              |
-| 0.0271     | 2500      | 0.132         | 0.2945          | 0.7569              |
-| 0.0325     | 3000      | 0.1161        | 0.2822          | 0.7636              |
-| 0.0379     | 3500      | 0.1105        | 0.2918          | 0.7580              |
-| 0.0433     | 4000      | 0.1072        | 0.2820          | 0.7597              |
-| 0.0487     | 4500      | 0.1061        | 0.2483          | 0.7661              |
-| 0.0542     | 5000      | 0.0991        | 0.2671          | 0.7600              |
-| 0.0596     | 5500      | 0.0971        | 0.2843          | 0.7595              |
-| 0.0650     | 6000      | 0.0953        | 0.2448          | 0.7640              |
-| 0.0704     | 6500      | 0.1015        | 0.3021          | 0.7632              |
-| 0.0758     | 7000      | 0.0985        | 0.2744          | 0.7616              |
-| 0.0812     | 7500      | 0.1009        | 0.2764          | 0.7615              |
-| 0.0866     | 8000      | 0.0984        | 0.2865          | 0.7608              |
-| 0.0921     | 8500      | 0.0947        | 0.3062          | 0.7600              |
-| 0.0975     | 9000      | 0.0914        | 0.2997          | 0.7584              |
-| 0.1029     | 9500      | 0.0896        | 0.2484          | 0.7617              |
-| 0.1083     | 10000     | 0.0846        | 0.2850          | 0.7594              |
-| 0.1137     | 10500     | 0.0907        | 0.2896          | 0.7571              |
-| 0.1191     | 11000     | 0.0859        | 0.2657          | 0.7599              |
-| 0.1245     | 11500     | 0.0875        | 0.2509          | 0.7620              |
-| 0.1300     | 12000     | 0.0849        | 0.2728          | 0.7620              |
-| 0.1354     | 12500     | 0.0788        | 0.2707          | 0.7587              |
-| 0.1408     | 13000     | 0.0804        | 0.2985          | 0.7567              |
-| 0.1462     | 13500     | 0.0815        | 0.2526          | 0.7620              |
-| 0.1516     | 14000     | 0.0783        | 0.2441          | 0.7655              |
-| 0.1570     | 14500     | 0.0791        | 0.2707          | 0.7645              |
-| 0.1625     | 15000     | 0.0797        | 0.2781          | 0.7576              |
-| 0.1679     | 15500     | 0.077         | 0.2624          | 0.7595              |
-| 0.1733     | 16000     | 0.0742        | 0.2882          | 0.7620              |
-| 0.1787     | 16500     | 0.0739        | 0.2654          | 0.7630              |
-| 0.1841     | 17000     | 0.0695        | 0.2832          | 0.7607              |
-| 0.1895     | 17500     | 0.0726        | 0.2595          | 0.7627              |
-| 0.1949     | 18000     | 0.0739        | 0.2376          | 0.7653              |
-| 0.2004     | 18500     | 0.0751        | 0.2671          | 0.7652              |
-| 0.2058     | 19000     | 0.0717        | 0.3013          | 0.7595              |
-| 0.2112     | 19500     | 0.0696        | 0.2538          | 0.7671              |
-| 0.2166     | 20000     | 0.0659        | 0.2569          | 0.7612              |
-| 0.2220     | 20500     | 0.0669        | 0.2595          | 0.7648              |
-| 0.2274     | 21000     | 0.0679        | 0.2231          | 0.7664              |
-| 0.2328     | 21500     | 0.0657        | 0.2732          | 0.7636              |
-| 0.2383     | 22000     | 0.0703        | 0.2658          | 0.7674              |
-| 0.2437     | 22500     | 0.0636        | 0.2582          | 0.7676              |
-| 0.2491     | 23000     | 0.0688        | 0.2586          | 0.7682              |
-| 0.2545     | 23500     | 0.0598        | 0.2612          | 0.7675              |
-| 0.2599     | 24000     | 0.0664        | 0.2581          | 0.7655              |
-| 0.2653     | 24500     | 0.0621        | 0.2393          | 0.7642              |
-| 0.2708     | 25000     | 0.0641        | 0.2309          | 0.7673              |
-| 0.2762     | 25500     | 0.0624        | 0.2346          | 0.7700              |
-| 0.2816     | 26000     | 0.0595        | 0.2179          | 0.7671              |
-| 0.2870     | 26500     | 0.0605        | 0.2332          | 0.7664              |
-| 0.2924     | 27000     | 0.0609        | 0.2227          | 0.7678              |
-| 0.2978     | 27500     | 0.0621        | 0.2312          | 0.7688              |
-| 0.3032     | 28000     | 0.0626        | 0.2404          | 0.7680              |
-| 0.3087     | 28500     | 0.063         | 0.2429          | 0.7672              |
-| 0.3141     | 29000     | 0.0601        | 0.2275          | 0.7671              |
-| 0.3195     | 29500     | 0.0617        | 0.2235          | 0.7663              |
-| 0.3249     | 30000     | 0.0581        | 0.2370          | 0.7698              |
-| 0.3303     | 30500     | 0.06          | 0.2450          | 0.7652              |
-| 0.3357     | 31000     | 0.0591        | 0.2851          | 0.7638              |
-| 0.3411     | 31500     | 0.0585        | 0.2718          | 0.7664              |
-| 0.3466     | 32000     | 0.0563        | 0.2532          | 0.7664              |
-| 0.3520     | 32500     | 0.059         | 0.2330          | 0.7689              |
-| 0.3574     | 33000     | 0.0545        | 0.2158          | 0.7695              |
-| 0.3628     | 33500     | 0.0567        | 0.2263          | 0.7672              |
-| 0.3682     | 34000     | 0.0566        | 0.2338          | 0.7682              |
-| 0.3736     | 34500     | 0.0586        | 0.2244          | 0.7696              |
-| 0.3791     | 35000     | 0.0559        | 0.2474          | 0.7671              |
-| 0.3845     | 35500     | 0.053         | 0.2332          | 0.7687              |
-| 0.3899     | 36000     | 0.0507        | 0.2258          | 0.7679              |
-| 0.3953     | 36500     | 0.0527        | 0.2240          | 0.7712              |
-| 0.4007     | 37000     | 0.0545        | 0.2229          | 0.7700              |
-| 0.4061     | 37500     | 0.0558        | 0.2119          | 0.7704              |
-| 0.4115     | 38000     | 0.0538        | 0.2611          | 0.7693              |
-| 0.4170     | 38500     | 0.0549        | 0.2336          | 0.7686              |
-| 0.4224     | 39000     | 0.0501        | 0.2316          | 0.7687              |
-| 0.4278     | 39500     | 0.0497        | 0.2289          | 0.7697              |
-| 0.4332     | 40000     | 0.0512        | 0.2299          | 0.7683              |
-| 0.4386     | 40500     | 0.0511        | 0.2654          | 0.7704              |
-| 0.4440     | 41000     | 0.0498        | 0.2272          | 0.7731              |
-| 0.4495     | 41500     | 0.053         | 0.2327          | 0.7696              |
-| 0.4549     | 42000     | 0.0487        | 0.2380          | 0.7715              |
-| 0.4603     | 42500     | 0.0518        | 0.2230          | 0.7724              |
-| 0.4657     | 43000     | 0.0488        | 0.2249          | 0.7703              |
-| 0.4711     | 43500     | 0.0529        | 0.2452          | 0.7716              |
-| 0.4765     | 44000     | 0.0497        | 0.2341          | 0.7720              |
-| 0.4819     | 44500     | 0.0486        | 0.2480          | 0.7696              |
-| 0.4874     | 45000     | 0.0518        | 0.2349          | 0.7715              |
-| 0.4928     | 45500     | 0.0471        | 0.2237          | 0.7720              |
-| 0.4982     | 46000     | 0.0483        | 0.2299          | 0.7712              |
-| 0.5036     | 46500     | 0.0462        | 0.2184          | 0.7705              |
-| 0.5090     | 47000     | 0.0497        | 0.2335          | 0.7718              |
-| 0.5144     | 47500     | 0.05          | 0.2302          | 0.7697              |
-| 0.5198     | 48000     | 0.0488        | 0.2252          | 0.7701              |
-| 0.5253     | 48500     | 0.045         | 0.2291          | 0.7687              |
-| 0.5307     | 49000     | 0.048         | 0.2135          | 0.7698              |
-| 0.5361     | 49500     | 0.0442        | 0.2215          | 0.7704              |
-| 0.5415     | 50000     | 0.0479        | 0.2233          | 0.7707              |
-| 0.5469     | 50500     | 0.0464        | 0.2275          | 0.7713              |
-| 0.5523     | 51000     | 0.0454        | 0.2175          | 0.7717              |
-| 0.5578     | 51500     | 0.0477        | 0.2152          | 0.7719              |
-| 0.5632     | 52000     | 0.0463        | 0.2364          | 0.7701              |
-| 0.5686     | 52500     | 0.0433        | 0.2430          | 0.7736              |
-| 0.5740     | 53000     | 0.0454        | 0.2328          | 0.7708              |
-| 0.5794     | 53500     | 0.0472        | 0.2283          | 0.7722              |
-| 0.5848     | 54000     | 0.0447        | 0.2320          | 0.7720              |
-| 0.5902     | 54500     | 0.0445        | 0.2404          | 0.7689              |
-| 0.5957     | 55000     | 0.0429        | 0.2353          | 0.7693              |
-| 0.6011     | 55500     | 0.0422        | 0.2366          | 0.7722              |
-| 0.6065     | 56000     | 0.0436        | 0.2321          | 0.7720              |
-| 0.6119     | 56500     | 0.0453        | 0.2250          | 0.7723              |
-| 0.6173     | 57000     | 0.0431        | 0.2219          | 0.7733              |
-| 0.6227     | 57500     | 0.0421        | 0.2244          | 0.7723              |
-| 0.6281     | 58000     | 0.0434        | 0.2137          | 0.7728              |
-| 0.6336     | 58500     | 0.0416        | 0.2181          | 0.7743              |
-| 0.6390     | 59000     | 0.0412        | 0.2230          | 0.7717              |
-| 0.6444     | 59500     | 0.0436        | 0.2116          | 0.7737              |
-| 0.6498     | 60000     | 0.0404        | 0.2114          | 0.7736              |
-| 0.6552     | 60500     | 0.041         | 0.2095          | 0.7736              |
-| 0.6606     | 61000     | 0.0408        | 0.2079          | 0.7741              |
-| 0.6661     | 61500     | 0.0408        | 0.2040          | 0.7756              |
-| 0.6715     | 62000     | 0.0404        | 0.2098          | 0.7733              |
-| 0.6769     | 62500     | 0.0418        | 0.2105          | 0.7741              |
-| 0.6823     | 63000     | 0.0402        | 0.2081          | 0.7741              |
-| 0.6877     | 63500     | 0.0394        | 0.2120          | 0.7742              |
-| 0.6931     | 64000     | 0.0418        | 0.2129          | 0.7742              |
-| 0.6985     | 64500     | 0.0406        | 0.2145          | 0.7753              |
-| 0.7040     | 65000     | 0.0382        | 0.2257          | 0.7741              |
-| 0.7094     | 65500     | 0.0373        | 0.2250          | 0.7756              |
-| 0.7148     | 66000     | 0.0382        | 0.2269          | 0.7732              |
-| **0.7202** | **66500** | **0.0405**    | **0.2087**      | **0.7764**          |
-| 0.7256     | 67000     | 0.042         | 0.2114          | 0.7753              |
-| 0.7310     | 67500     | 0.0389        | 0.2138          | 0.7748              |
-| 0.7364     | 68000     | 0.0339        | 0.2084          | 0.7761              |
-| 0.7419     | 68500     | 0.0379        | 0.2090          | 0.7760              |
-| 0.7473     | 69000     | 0.0369        | 0.2161          | 0.7742              |
-| 0.7527     | 69500     | 0.0354        | 0.2226          | 0.7748              |
-| 0.7581     | 70000     | 0.0396        | 0.2191          | 0.7753              |
-| 0.7635     | 70500     | 0.0356        | 0.2195          | 0.7759              |
-| 0.7689     | 71000     | 0.0359        | 0.2182          | 0.7760              |
-| 0.7744     | 71500     | 0.0389        | 0.2187          | 0.7753              |
-| 0.7798     | 72000     | 0.0366        | 0.2194          | 0.7753              |
-| 0.7852     | 72500     | 0.0351        | 0.2198          | 0.7749              |
-| 0.7906     | 73000     | 0.038         | 0.2175          | 0.7754              |
-| 0.7960     | 73500     | 0.0378        | 0.2172          | 0.7756              |
-| 0.8014     | 74000     | 0.0376        | 0.2174          | 0.7754              |
-| 0.8068     | 74500     | 0.038         | 0.2176          | 0.7753              |
-| 0.8123     | 75000     | 0.0379        | 0.2174          | 0.7755              |
-
-* The bold row denotes the saved checkpoint.
-</details>
 
 ### Framework Versions
 - Python: 3.12.3

config.json

@@ -1,45 +1,25 @@
 {
   "architectures": [
-    "ModernBertModel"
+    "BertModel"
   ],
-  "attention_bias": false,
-  "attention_dropout": 0.0,
-  "bos_token_id": 50281,
-  "classifier_activation": "gelu",
-  "classifier_bias": false,
-  "classifier_dropout": 0.0,
-  "classifier_pooling": "cls",
-  "cls_token_id": 50281,
-  "decoder_bias": true,
-  "deterministic_flash_attn": false,
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
   "dtype": "bfloat16",
-  "embedding_dropout": 0.0,
-  "eos_token_id": 50282,
-  "global_attn_every_n_layers": 3,
-  "global_rope_theta": 160000.0,
   "gradient_checkpointing": false,
-  "hidden_activation": "gelu",
-  "hidden_size": 1024,
-  "initializer_cutoff_factor": 2.0,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
   "initializer_range": 0.02,
-  "intermediate_size": 2624,
-  "layer_norm_eps": 1e-05,
-  "local_attention": 128,
-  "local_rope_theta": 10000.0,
-  "max_position_embeddings": 8192,
-  "mlp_bias": false,
-  "mlp_dropout": 0.0,
-  "model_type": "modernbert",
-  "norm_bias": false,
-  "norm_eps": 1e-05,
-  "num_attention_heads": 16,
-  "num_hidden_layers": 28,
-  "pad_token_id": 50283,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
   "position_embedding_type": "absolute",
-  "repad_logits_with_grad": false,
-  "sep_token_id": 50282,
-  "sparse_pred_ignore_index": -100,
-  "sparse_prediction": false,
   "transformers_version": "4.56.0",
-  "vocab_size": 50368
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
 }

config_sentence_transformers.json

@@ -1,10 +1,10 @@
 {
-  "model_type": "SentenceTransformer",
   "__version__": {
     "sentence_transformers": "5.1.0",
     "transformers": "4.56.0",
     "pytorch": "2.8.0+cu128"
   },
+  "model_type": "SentenceTransformer",
   "prompts": {
     "query": "",
     "document": ""

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2304eb08c679af236a8a9179f0e08d478a4d1958873dd0990efbc0ca883decab
-size 789580328
+oid sha256:2d7e72835b966eaeabd3532bf9069d0626fc4f4ef5fef0f6eac90c7402f42d6f
+size 45437864

modules.json

@@ -10,5 +10,11 @@
     "name": "1",
     "path": "1_Pooling",
     "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
   }
 ]

special_tokens_map.json

@@ -8,7 +8,7 @@
   },
   "mask_token": {
     "content": "[MASK]",
-    "lstrip": true,
+    "lstrip": false,
     "normalized": false,
     "rstrip": false,
     "single_word": false

tokenizer_config.json

@@ -1,230 +1,14 @@
 {
   "added_tokens_decoder": {
     "0": {
-      "content": "|||IP_ADDRESS|||",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "1": {
-      "content": "<|padding|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "50254": {
-      "content": "                        ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50255": {
-      "content": "                       ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50256": {
-      "content": "                      ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50257": {
-      "content": "                     ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50258": {
-      "content": "                    ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50259": {
-      "content": "                   ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50260": {
-      "content": "                  ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50261": {
-      "content": "                 ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50262": {
-      "content": "                ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50263": {
-      "content": "               ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50264": {
-      "content": "              ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50265": {
-      "content": "             ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50266": {
-      "content": "            ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50267": {
-      "content": "           ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50268": {
-      "content": "          ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50269": {
-      "content": "         ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50270": {
-      "content": "        ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50271": {
-      "content": "       ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50272": {
-      "content": "      ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50273": {
-      "content": "     ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50274": {
-      "content": "    ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50275": {
-      "content": "   ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50276": {
-      "content": "  ",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50277": {
-      "content": "|||EMAIL_ADDRESS|||",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50278": {
-      "content": "|||PHONE_NUMBER|||",
-      "lstrip": false,
-      "normalized": true,
-      "rstrip": false,
-      "single_word": false,
-      "special": false
-    },
-    "50279": {
-      "content": "<|endoftext|>",
+      "content": "[PAD]",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,
       "single_word": false,
       "special": true
     },
-    "50280": {
+    "100": {
       "content": "[UNK]",
       "lstrip": false,
       "normalized": false,
@@ -232,7 +16,7 @@
       "single_word": false,
       "special": true
     },
-    "50281": {
+    "101": {
       "content": "[CLS]",
       "lstrip": false,
       "normalized": false,
@@ -240,7 +24,7 @@
       "single_word": false,
       "special": true
     },
-    "50282": {
+    "102": {
       "content": "[SEP]",
       "lstrip": false,
       "normalized": false,
@@ -248,699 +32,34 @@
       "single_word": false,
       "special": true
     },
-    "50283": {
-      "content": "[PAD]",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "50284": {
+    "103": {
       "content": "[MASK]",
-      "lstrip": true,
+      "lstrip": false,
       "normalized": false,
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