Add new CrossEncoder 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
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,549 @@
+---
+tags:
+- sentence-transformers
+- cross-encoder
+- reranker
+- generated_from_trainer
+- dataset_size:769572
+- loss:BinaryCrossEntropyLoss
+base_model: BAAI/bge-reranker-v2-m3
+pipeline_tag: text-ranking
+library_name: sentence-transformers
+metrics:
+- map
+- mrr@10
+- ndcg@10
+model-index:
+- name: CrossEncoder based on BAAI/bge-reranker-v2-m3
+  results:
+  - task:
+      type: cross-encoder-reranking
+      name: Cross Encoder Reranking
+    dataset:
+      name: query note test
+      type: query_note_test
+    metrics:
+    - type: map
+      value: 0.45654587062161356
+      name: Map
+    - type: mrr@10
+      value: 0.5283685579312956
+      name: Mrr@10
+    - type: ndcg@10
+      value: 0.527108528024005
+      name: Ndcg@10
+  - task:
+      type: cross-encoder-reranking
+      name: Cross Encoder Reranking
+    dataset:
+      name: query note val
+      type: query_note_val
+    metrics:
+    - type: map
+      value: 0.45724051914340746
+      name: Map
+    - type: mrr@10
+      value: 0.5246903296465979
+      name: Mrr@10
+    - type: ndcg@10
+      value: 0.5328170850876233
+      name: Ndcg@10
+---
+
+# CrossEncoder based on BAAI/bge-reranker-v2-m3
+
+This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Cross Encoder
+- **Base model:** [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) <!-- at revision 953dc6f6f85a1b2dbfca4c34a2796e7dde08d41e -->
+- **Maximum Sequence Length:** 512 tokens
+- **Number of Output Labels:** 1 label
+- **Supported Modality:** Text
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
+- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
+
+### Full Model Architecture
+
+```
+CrossEncoder(
+  (0): Transformer({'transformer_task': 'sequence-classification', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'logits'}}, 'module_output_name': 'scores', 'architecture': 'XLMRobertaForSequenceClassification'})
+)
+```
+
+## 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 CrossEncoder
+
+# Download from the 🤗 Hub
+model = CrossEncoder("steerrec/bge-reranker-v2-m3-query-note")
+# Get scores for pairs of inputs
+pairs = [
+    ['infp男和infj女', '谁懂啊啊啊‼️💗INFP×INFJ相处好戳我\n绿老头和小蝴蝶都是高敏易碎人群，消息秒回啊，朋友圈点赞啊，这种细微且偏爱的行为，都能让对方感到安心和减少内耗。\n小蝴蝶的话，有事情就不要藏着掖着，对绿老头也不要有过多的试探行为，有问题就直接问，直接说，只要把事情拖到情绪都上来了，那这问题就更难解决了。因为绿老头只是看起来淡然，但其实他们的内心是很火热躁动的，他们只是不好意思主动表达。绿老头得学会调整，明知道小蝴蝶容易想多内耗，那就多主动表现情绪，不要让小蝴蝶觉得你对他淡淡的，要是能偶尔打个只球，明确的表达一下内心，那就更好了。#心理[话题]# #mbti[话题]# #infp[话题]# #infp日常[话题]# #infp和infj[话题]# #INFJ[话题]# #infj的世界[话题]# #我的日常[话题]# #温暖治愈[话题]# '],
+    ['电动车远光灯刺眼反击', '电动车在这些情况下是全责哦！注意了哦！\n骑电动车一定要小心这些情况哦！[暗中观察R]#交通事故理赔[话题]# #交通事故[话题]# #法律求助[话题]# #电动车[话题]# #法律咨询[话题]# #交通安全[话题]# '],
+    ['电动车远光灯刺眼反击', '支付宝上这个骑行险有用吗\n#车险[话题]# #电动车骑行险[话题]# #支付宝[话题]# '],
+    ['牛奶品牌排名', '注意❗注意❗杯子到货，买就送📢\n杯子已经到货啦📣\n依然还是35.9到手2瓶4斤装的鲜奶，在额外赠送2个mini玻璃杯哦~\n顺丰冷链发货，包邮到家📦\n\xa0#乍甸牛奶[话题]#\xa0\xa0#云南游[话题]#\xa0\xa0#鲜奶[话题]#\xa0\xa0#可爱杯子[话题]#\xa0\xa0#杯子分享[话题]#\xa0\xa0#杯子控必入系列[话题]#\xa0\xa0#我就是个杯子控[话题]#\xa0\xa0#杯子[话题]#\xa0\xa0#鲜奶酸奶怎么挑[话��]#\xa0\xa0#鲜奶推荐[话题]#\xa0\xa0#鲜牛乳[话题]#\xa0\xa0#乍甸牛奶福利种草官[话题]#\xa0\xa0#乍甸牛奶也很好喝[话题]#\xa0\xa0#乍甸鲜奶[话题]#\xa0\t\n'],
+    ['mbti人格', 'INFP小蝴蝶🦋请谨慎破防😅\n感觉本infp的确心灵上有些许脆弱，在面对朋友或者家人，别人的一句批评或者不认同，会影响我一天的心情～感觉这个习惯跟刻在骨子里一样，一边安慰自己，却一边焦虑😮\u200d💨很难想象有时候自己却很开朗乐观，其实内心很脆弱，一点就破⊙﹏⊙\n\t\n内容纯属娱乐🌚如有雷同纯属巧合🌚\n请大家对号入座哈哈哈哈😂#MBTI16型人格[话题]# #mbti梗图[话题]# #infp精神世界[话题]# #infp日常[话题]# '],
+]
+scores = model.predict(pairs)
+print(scores)
+# [0.3757 0.2134 0.1656 0.179  0.272 ]
+
+# Or rank different texts based on similarity to a single text
+ranks = model.rank(
+    'infp男和infj女',
+    [
+        '谁懂啊啊啊‼️💗INFP×INFJ相处好戳我\n绿老头和小蝴蝶都是高敏易碎人群，消息秒回啊，朋友圈点赞啊，这种细微且偏爱的行为，都能让对方感到安心和减少内耗。\n小蝴蝶的话，有事情就不要藏着掖着，对绿老头也不要有过多的试探行为，有问题就直接问，直接说，只要把事情拖到情绪都上来了，那这问题就更难解决了。因为绿老头只是看起来淡然，但其实他们的内心是很火热躁动的，他们只是不好意思主动表达。绿老头得学会调整，明知道小蝴蝶容易想多内耗，那就多主动表现情绪，不要让小蝴蝶觉得你对他淡淡的，要是能偶尔打个只球，明确的表达一下内心，那就更好了。#心理[话题]# #mbti[话题]# #infp[话题]# #infp日常[话题]# #infp和infj[话题]# #INFJ[话题]# #infj的世界[话题]# #我的日常[话题]# #温暖治愈[话题]# ',
+        '电动车在这些情况下是全责哦！注意了哦！\n骑电动车一定要小心这些情况哦！[暗中观察R]#交通事故理赔[话题]# #交通事故[话题]# #法律求助[话题]# #电动车[话题]# #法律咨询[话题]# #交通安全[话题]# ',
+        '支付宝上这个骑行险有用吗\n#车险[话题]# #电动车骑行险[话题]# #支付宝[话题]# ',
+        '注意❗注意❗杯子到货，买就送📢\n杯子已经到货啦📣\n依然还是35.9到手2瓶4斤装的鲜奶，在额外赠送2个mini玻璃杯哦~\n顺丰冷链发货，包邮到家📦\n\xa0#乍甸牛奶[话题]#\xa0\xa0#云南游[话题]#\xa0\xa0#鲜奶[话题]#\xa0\xa0#可爱杯子[话题]#\xa0\xa0#杯子分享[话题]#\xa0\xa0#杯子控必入系列[话题]#\xa0\xa0#我就是个杯子控[话题]#\xa0\xa0#杯子[话题]#\xa0\xa0#鲜奶酸奶怎么挑[话题]#\xa0\xa0#鲜奶推荐[话题]#\xa0\xa0#鲜牛乳[话题]#\xa0\xa0#乍甸牛奶福利种草官[话题]#\xa0\xa0#乍甸牛奶也很好喝[话题]#\xa0\xa0#乍甸鲜奶[话题]#\xa0\t\n',
+        'INFP小蝴蝶🦋请谨慎破防😅\n感觉本infp的确心灵上有些许脆弱，在面对朋友或者家人，别人的一句批评或者不认同，会影响我一天的心情～感觉这个习惯跟刻在骨子里一样，一边安慰自己，却一边焦虑😮\u200d💨很难想象有时候自己却很开朗乐观，其实内心很脆弱，一点就破⊙﹏⊙\n\t\n内容纯属娱乐🌚如有雷同纯属巧合🌚\n请大家对号入座哈哈哈哈😂#MBTI16型人格[话题]# #mbti梗图[话题]# #infp精神世界[话题]# #infp日常[话题]# ',
+    ]
+)
+# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Cross Encoder Reranking
+
+* Datasets: `query_note_test` and `query_note_val`
+* Evaluated with [<code>CrossEncoderRerankingEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderRerankingEvaluator) with these parameters:
+  ```json
+  {
+      "at_k": 10
+  }
+  ```
+
+| Metric      | query_note_test | query_note_val |
+|:------------|:----------------|:---------------|
+| map         | 0.4565          | 0.4572         |
+| mrr@10      | 0.5284          | 0.5247         |
+| **ndcg@10** | **0.5271**      | **0.5328**     |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 769,572 training samples
+* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
+* Approximate statistics based on the first 100 samples:
+  |          | sentence1                                                                        | sentence2                                                                            | label                                                         |
+  |:---------|:---------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------|
+  | type     | string                                                                           | string                                                                               | float                                                         |
+  | modality | text                                                                             | text                                                                                 |                                                               |
+  | details  | <ul><li>min: 5 tokens</li><li>mean: 7.92 tokens</li><li>max: 13 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 208.42 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.0</li><li>max: 0.0</li></ul> |
+* Samples:
+  | sentence1                | sentence2                                                                                                                                                                                                                                                                                                                                                                                              | label            |
+  |:-------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
+  | <code>infp男和infj女</code> | <code>谁懂啊啊啊‼️💗INFP×INFJ相处好戳我<br>绿老头和小蝴蝶都是高敏易碎人群，消息秒回啊，朋友圈点赞啊，这种细微且偏爱的行为，都能让对方感到安心和减少内耗。<br>小蝴蝶的话，有事情就不要藏着掖着，对绿老头也不要有过多的试探行为，有问题就直接问，直接说，只要把事情拖到情绪都上来了，那这问题就更难解决了。因为绿老头只是看起来淡然，但其实他们的内心是很火热躁动的，他们只是不好意思主动表达。绿老头得学会调整，明知道小蝴蝶容易想多内耗，那就多主动表现情绪，不要让小蝴蝶觉得你对他淡淡的，要是能偶尔打个只球，明确的表达一下内心，那就更好了。#心理[话题]# #mbti[话题]# #infp[话题]# #infp日常[话题]# #infp和infj[话题]# #INFJ[话题]# #infj的世界[话题]# #我的日常[话题]# #温暖治愈[话题]# </code> | <code>0.0</code> |
+  | <code>电动车远光灯刺眼反击</code>  | <code>电动车在这些情况下是全责哦！注意了哦！<br>骑电动车一定要小心这些情况哦！[暗中观察R]#交通事故理赔[话题]# #交通事故[话题]# #法律求助[话题]# #电动车[话题]# #法律咨询[话题]# #交通安全[话题]# </code>                                                                                                                                                                                                                                                                          | <code>0.0</code> |
+  | <code>电动车远光灯刺眼反击</code>  | <code>支付宝上这个骑行险有用吗<br>#车险[话题]# #电动车骑行险[话题]# #支付宝[话题]# </code>                                                                                                                                                                                                                                                                                                                                          | <code>0.0</code> |
+* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
+  ```json
+  {
+      "activation_fn": "torch.nn.modules.linear.Identity",
+      "pos_weight": null
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 32
+- `learning_rate`: 0.0001
+- `weight_decay`: 0.01
+- `num_train_epochs`: 1
+- `lr_scheduler_type`: cosine
+- `warmup_ratio`: 0.05
+- `seed`: 3407
+- `bf16`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `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`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 0.0001
+- `weight_decay`: 0.01
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `lr_scheduler_type`: cosine
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.05
+- `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`: 3407
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: True
+- `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`: 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
+- `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
+- `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`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch  | Step  | Training Loss | query_note_test_ndcg@10 | query_note_val_ndcg@10 |
+|:------:|:-----:|:-------------:|:-----------------------:|:----------------------:|
+| -1     | -1    | -             | 0.5206                  | -                      |
+| 0.7048 | 16950 | 0.6932        | -                       | -                      |
+| 0.7069 | 17000 | 0.5323        | -                       | -                      |
+| 0.7089 | 17050 | 0.5209        | -                       | -                      |
+| 0.7110 | 17100 | 0.5281        | -                       | -                      |
+| 0.7131 | 17150 | 0.5267        | -                       | -                      |
+| 0.7152 | 17200 | 0.5124        | -                       | -                      |
+| 0.7173 | 17250 | 0.5199        | -                       | -                      |
+| 0.7193 | 17300 | 0.5189        | -                       | -                      |
+| 0.7214 | 17350 | 0.5059        | -                       | -                      |
+| 0.7235 | 17400 | 0.5326        | -                       | -                      |
+| 0.7256 | 17450 | 0.5159        | -                       | -                      |
+| 0.7277 | 17500 | 0.5246        | -                       | -                      |
+| 0.7297 | 17550 | 0.5128        | -                       | -                      |
+| 0.7318 | 17600 | 0.5078        | -                       | -                      |
+| 0.7339 | 17650 | 0.4966        | -                       | -                      |
+| 0.7360 | 17700 | 0.506         | -                       | -                      |
+| 0.7380 | 17750 | 0.499         | -                       | -                      |
+| 0.7401 | 17800 | 0.5069        | -                       | -                      |
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+| 0.7443 | 17900 | 0.5124        | -                       | -                      |
+| 0.7464 | 17950 | 0.522         | -                       | -                      |
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+| 0.7547 | 18150 | 0.5151        | -                       | -                      |
+| 0.7568 | 18200 | 0.4804        | -                       | -                      |
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+| 0.7796 | 18750 | 0.5145        | -                       | -                      |
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+| 0.7838 | 18850 | 0.5188        | -                       | -                      |
+| 0.7859 | 18900 | 0.501         | -                       | -                      |
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+| 0.9376 | 22550 | 0.4938        | -                       | -                      |
+| 0.9397 | 22600 | 0.5086        | -                       | -                      |
+| 0.9418 | 22650 | 0.457         | -                       | -                      |
+| 0.9439 | 22700 | 0.5185        | -                       | -                      |
+| 0.9459 | 22750 | 0.5268        | -                       | -                      |
+| 0.9480 | 22800 | 0.4872        | -                       | -                      |
+| 0.9501 | 22850 | 0.5048        | -                       | -                      |
+| 0.9522 | 22900 | 0.5103        | -                       | -                      |
+| 0.9543 | 22950 | 0.5236        | -                       | -                      |
+| 0.9563 | 23000 | 0.5049        | -                       | -                      |
+| 0.9584 | 23050 | 0.5041        | -                       | -                      |
+| 0.9605 | 23100 | 0.5066        | -                       | -                      |
+| 0.9626 | 23150 | 0.5206        | -                       | -                      |
+| 0.9647 | 23200 | 0.4732        | -                       | -                      |
+| 0.9667 | 23250 | 0.4881        | -                       | -                      |
+| 0.9688 | 23300 | 0.5099        | -                       | -                      |
+| 0.9709 | 23350 | 0.5226        | -                       | -                      |
+| 0.9730 | 23400 | 0.5322        | -                       | -                      |
+| 0.9751 | 23450 | 0.4993        | -                       | -                      |
+| 0.9771 | 23500 | 0.4856        | -                       | -                      |
+| 0.9792 | 23550 | 0.4727        | -                       | -                      |
+| 0.9813 | 23600 | 0.5093        | -                       | -                      |
+| 0.9834 | 23650 | 0.5073        | -                       | -                      |
+| 0.9854 | 23700 | 0.5153        | -                       | -                      |
+| 0.9875 | 23750 | 0.4979        | -                       | -                      |
+| 0.9896 | 23800 | 0.4961        | -                       | -                      |
+| 0.9917 | 23850 | 0.5093        | -                       | -                      |
+| 0.9938 | 23900 | 0.4811        | -                       | -                      |
+| 0.9958 | 23950 | 0.5008        | -                       | -                      |
+| 0.9979 | 24000 | 0.5151        | -                       | -                      |
+| 1.0    | 24050 | 0.5318        | -                       | 0.5328                 |
+| -1     | -1    | -             | 0.5271                  | -                      |
+
+</details>
+
+### Training Time
+- **Training**: 57.2 minutes
+
+### Framework Versions
+- Python: 3.12.3
+- Sentence Transformers: 5.5.1
+- Transformers: 4.56.2
+- PyTorch: 2.11.0+cu128
+- Accelerate: 1.13.0
+- Datasets: 4.3.0
+- Tokenizers: 0.22.2
+
+## Additional Resources
+
+- [Training and Finetuning Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-reranker): the end-to-end guide for training or finetuning Cross Encoder (reranker) models.
+- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video reranker models through the same API.
+- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): training multimodal Cross Encoders.
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,33 @@
+{
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 8194,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.56.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

config_sentence_transformers.json

@@ -0,0 +1,11 @@
+{
+  "__version__": {
+    "pytorch": "2.11.0+cu128",
+    "sentence_transformers": "5.5.1",
+    "transformers": "4.56.2"
+  },
+  "activation_fn": "torch.nn.modules.activation.Sigmoid",
+  "default_prompt_name": null,
+  "model_type": "CrossEncoder",
+  "prompts": {}
+}

model.safetensors

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+oid sha256:965ad8042c9f8d96bb7406e42110d3d5579e4f3c811977191f5fd77d6f24ad2d
+size 2271071852

modules.json

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+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "sequence-classification",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "logits"
+        }
+    },
+    "module_output_name": "scores"
+}

sentencepiece.bpe.model

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+version https://git-lfs.github.com/spec/v1
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+size 5069051

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
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+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cf44dabfaa82b1276a7af64a2ea2c76c047d560cf7bfb5711d6135382372c93d
+size 17083153

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
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+      "lstrip": true,
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}