| --- |
| tags: |
| - sentence-transformers |
| - cross-encoder |
| - generated_from_trainer |
| - dataset_size:17639 |
| - loss:BinaryCrossEntropyLoss |
| base_model: cross-encoder/msmarco-MiniLM-L6-en-de-v1 |
| pipeline_tag: text-ranking |
| library_name: sentence-transformers |
| metrics: |
| - pearson |
| - spearman |
| model-index: |
| - name: CrossEncoder based on cross-encoder/msmarco-MiniLM-L6-en-de-v1 |
| results: |
| - task: |
| type: cross-encoder-correlation |
| name: Cross Encoder Correlation |
| dataset: |
| name: onet validation |
| type: onet-validation |
| metrics: |
| - type: pearson |
| value: 0.8246902137614378 |
| name: Pearson |
| - type: spearman |
| value: 0.8073346678301418 |
| name: Spearman |
| - type: pearson |
| value: 0.8080619777425957 |
| name: Pearson |
| - type: spearman |
| value: 0.7875635794780041 |
| name: Spearman |
| --- |
| |
| # CrossEncoder based on cross-encoder/msmarco-MiniLM-L6-en-de-v1 |
|
|
| This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/msmarco-MiniLM-L6-en-de-v1](https://huggingface.co/cross-encoder/msmarco-MiniLM-L6-en-de-v1) on the csv dataset 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:** [cross-encoder/msmarco-MiniLM-L6-en-de-v1](https://huggingface.co/cross-encoder/msmarco-MiniLM-L6-en-de-v1) <!-- at revision 9eb610d90d409cfefb7422e13debd405f8465af6 --> |
| - **Maximum Sequence Length:** 512 tokens |
| - **Number of Output Labels:** 1 label |
| - **Training Dataset:** |
| - csv |
| <!-- - **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/UKPLab/sentence-transformers) |
| - **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder) |
|
|
| ## 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("cross_encoder_model_id") |
| # Get scores for pairs of texts |
| pairs = [ |
| ['Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', "Direct or coordinate an organization's financial or budget activities to fund operations, maximize investments, or increase efficiency."], |
| ['Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', 'Confer with board members, organization officials, or staff members to discuss issues, coordinate activities, or resolve problems.'], |
| ['Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', 'Prepare budgets for approval, including those for funding or implementation of programs.'], |
| ['Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', 'Direct, plan, or implement policies, objectives, or activities of organizations or businesses to ensure continuing operations, to maximize returns on investments, or to increase productivity.'], |
| ['Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', 'Prepare or present reports concerning activities, expenses, budgets, government statutes or rulings, or other items affecting businesses or program services.'], |
| ] |
| scores = model.predict(pairs) |
| print(scores.shape) |
| # (5,) |
| |
| # Or rank different texts based on similarity to a single text |
| ranks = model.rank( |
| 'Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.', |
| [ |
| "Direct or coordinate an organization's financial or budget activities to fund operations, maximize investments, or increase efficiency.", |
| 'Confer with board members, organization officials, or staff members to discuss issues, coordinate activities, or resolve problems.', |
| 'Prepare budgets for approval, including those for funding or implementation of programs.', |
| 'Direct, plan, or implement policies, objectives, or activities of organizations or businesses to ensure continuing operations, to maximize returns on investments, or to increase productivity.', |
| 'Prepare or present reports concerning activities, expenses, budgets, government statutes or rulings, or other items affecting businesses or program services.', |
| ] |
| ) |
| # [{'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 Correlation |
|
|
| * Dataset: `onet-validation` |
| * Evaluated with [<code>CrossEncoderCorrelationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderCorrelationEvaluator) |
|
|
| | Metric | Value | |
| |:-------------|:-----------| |
| | pearson | 0.8247 | |
| | **spearman** | **0.8073** | |
|
|
| #### Cross Encoder Correlation |
|
|
| * Dataset: `onet-validation` |
| * Evaluated with [<code>CrossEncoderCorrelationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderCorrelationEvaluator) |
|
|
| | Metric | Value | |
| |:-------------|:-----------| |
| | pearson | 0.8081 | |
| | **spearman** | **0.7876** | |
|
|
| <!-- |
| ## 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 |
|
|
| #### csv |
|
|
| * Dataset: csv |
| * Size: 17,639 training samples |
| * Columns: <code>query</code>, <code>task</code>, and <code>score</code> |
| * Approximate statistics based on the first 1000 samples: |
| | | query | task | score | |
| |:--------|:--------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------|:----------------------------------------------------------------| |
| | type | string | string | float | |
| | details | <ul><li>min: 105 characters</li><li>mean: 235.78 characters</li><li>max: 562 characters</li></ul> | <ul><li>min: 20 characters</li><li>mean: 103.24 characters</li><li>max: 317 characters</li></ul> | <ul><li>min: 0.42</li><li>mean: 0.8</li><li>max: 0.98</li></ul> | |
| * Samples: |
| | query | task | score | |
| |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------| |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Direct or coordinate an organization's financial or budget activities to fund operations, maximize investments, or increase efficiency.</code> | <code>0.8242</code> | |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Confer with board members, organization officials, or staff members to discuss issues, coordinate activities, or resolve problems.</code> | <code>0.84055</code> | |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Prepare budgets for approval, including those for funding or implementation of programs.</code> | <code>0.89705</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 |
| } |
| ``` |
|
|
| ### Evaluation Dataset |
|
|
| #### csv |
|
|
| * Dataset: csv |
| * Size: 1,764 evaluation samples |
| * Columns: <code>query</code>, <code>task</code>, and <code>score</code> |
| * Approximate statistics based on the first 1000 samples: |
| | | query | task | score | |
| |:--------|:--------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------|:----------------------------------------------------------------| |
| | type | string | string | float | |
| | details | <ul><li>min: 105 characters</li><li>mean: 235.78 characters</li><li>max: 562 characters</li></ul> | <ul><li>min: 20 characters</li><li>mean: 103.24 characters</li><li>max: 317 characters</li></ul> | <ul><li>min: 0.42</li><li>mean: 0.8</li><li>max: 0.98</li></ul> | |
| * Samples: |
| | query | task | score | |
| |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------| |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Direct or coordinate an organization's financial or budget activities to fund operations, maximize investments, or increase efficiency.</code> | <code>0.8242</code> | |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Confer with board members, organization officials, or staff members to discuss issues, coordinate activities, or resolve problems.</code> | <code>0.84055</code> | |
| | <code>Chief Executives:Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. Plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.</code> | <code>Prepare budgets for approval, including those for funding or implementation of programs.</code> | <code>0.89705</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 |
|
|
| - `eval_strategy`: steps |
| - `num_train_epochs`: 4 |
| - `warmup_ratio`: 0.1 |
| - `bf16`: True |
|
|
| #### 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`: 8 |
| - `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`: 5e-05 |
| - `weight_decay`: 0.0 |
| - `adam_beta1`: 0.9 |
| - `adam_beta2`: 0.999 |
| - `adam_epsilon`: 1e-08 |
| - `max_grad_norm`: 1.0 |
| - `num_train_epochs`: 4 |
| - `max_steps`: -1 |
| - `lr_scheduler_type`: linear |
| - `lr_scheduler_kwargs`: {} |
| - `warmup_ratio`: 0.1 |
| - `warmup_steps`: 0 |
| - `log_level`: passive |
| - `log_level_replica`: warning |
| - `log_on_each_node`: True |
| - `logging_nan_inf_filter`: True |
| - `save_safetensors`: True |
| - `save_on_each_node`: False |
| - `save_only_model`: False |
| - `restore_callback_states_from_checkpoint`: False |
| - `no_cuda`: False |
| - `use_cpu`: False |
| - `use_mps_device`: False |
| - `seed`: 42 |
| - `data_seed`: None |
| - `jit_mode_eval`: False |
| - `use_ipex`: False |
| - `bf16`: 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} |
| - `tp_size`: 0 |
| - `fsdp_transformer_layer_cls_to_wrap`: None |
| - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} |
| - `deepspeed`: None |
| - `label_smoothing_factor`: 0.0 |
| - `optim`: adamw_torch |
| - `optim_args`: None |
| - `adafactor`: False |
| - `group_by_length`: False |
| - `length_column_name`: length |
| - `ddp_find_unused_parameters`: None |
| - `ddp_bucket_cap_mb`: None |
| - `ddp_broadcast_buffers`: False |
| - `dataloader_pin_memory`: True |
| - `dataloader_persistent_workers`: False |
| - `skip_memory_metrics`: True |
| - `use_legacy_prediction_loop`: False |
| - `push_to_hub`: False |
| - `resume_from_checkpoint`: None |
| - `hub_model_id`: None |
| - `hub_strategy`: every_save |
| - `hub_private_repo`: None |
| - `hub_always_push`: False |
| - `gradient_checkpointing`: False |
| - `gradient_checkpointing_kwargs`: None |
| - `include_inputs_for_metrics`: False |
| - `include_for_metrics`: [] |
| - `eval_do_concat_batches`: True |
| - `fp16_backend`: auto |
| - `push_to_hub_model_id`: None |
| - `push_to_hub_organization`: None |
| - `mp_parameters`: |
| - `auto_find_batch_size`: False |
| - `full_determinism`: False |
| - `torchdynamo`: None |
| - `ray_scope`: last |
| - `ddp_timeout`: 1800 |
| - `torch_compile`: False |
| - `torch_compile_backend`: None |
| - `torch_compile_mode`: None |
| - `include_tokens_per_second`: False |
| - `include_num_input_tokens_seen`: False |
| - `neftune_noise_alpha`: None |
| - `optim_target_modules`: None |
| - `batch_eval_metrics`: False |
| - `eval_on_start`: False |
| - `use_liger_kernel`: False |
| - `eval_use_gather_object`: False |
| - `average_tokens_across_devices`: False |
| - `prompts`: None |
| - `batch_sampler`: batch_sampler |
| - `multi_dataset_batch_sampler`: proportional |
|
|
| </details> |
|
|
| ### Training Logs |
| <details><summary>Click to expand</summary> |
|
|
| | Epoch | Step | Training Loss | Validation Loss | onet-validation_spearman | |
| |:------:|:----:|:-------------:|:---------------:|:------------------------:| |
| | -1 | -1 | - | - | 0.0090 | |
| | 0.0091 | 20 | 1.2693 | - | - | |
| | 0.0181 | 40 | 1.3548 | - | - | |
| | 0.0272 | 60 | 1.0328 | - | - | |
| | 0.0363 | 80 | 0.9504 | 0.8379 | 0.0108 | |
| | 0.0454 | 100 | 0.9183 | - | - | |
| | 0.0544 | 120 | 0.697 | - | - | |
| | 0.0635 | 140 | 0.625 | - | - | |
| | 0.0726 | 160 | 0.5337 | 0.5489 | 0.0368 | |
| | 0.0816 | 180 | 0.5008 | - | - | |
| | 0.0907 | 200 | 0.4894 | - | - | |
| | 0.0998 | 220 | 0.5352 | - | - | |
| | 0.1088 | 240 | 0.4994 | 0.5040 | 0.0981 | |
| | 0.1179 | 260 | 0.4857 | - | - | |
| | 0.1270 | 280 | 0.5122 | - | - | |
| | 0.1361 | 300 | 0.517 | - | - | |
| | 0.1451 | 320 | 0.5156 | 0.4994 | 0.1470 | |
| | 0.1542 | 340 | 0.4859 | - | - | |
| | 0.1633 | 360 | 0.4842 | - | - | |
| | 0.1723 | 380 | 0.5138 | - | - | |
| | 0.1814 | 400 | 0.5142 | 0.5011 | 0.1403 | |
| | 0.1905 | 420 | 0.4948 | - | - | |
| | 0.1995 | 440 | 0.499 | - | - | |
| | 0.2086 | 460 | 0.4732 | - | - | |
| | 0.2177 | 480 | 0.5066 | 0.5007 | 0.1681 | |
| | 0.2268 | 500 | 0.5014 | - | - | |
| | 0.2358 | 520 | 0.4819 | - | - | |
| | 0.2449 | 540 | 0.4937 | - | - | |
| | 0.2540 | 560 | 0.5056 | 0.4974 | 0.2359 | |
| | 0.2630 | 580 | 0.4986 | - | - | |
| | 0.2721 | 600 | 0.5066 | - | - | |
| | 0.2812 | 620 | 0.4776 | - | - | |
| | 0.2902 | 640 | 0.4845 | 0.5024 | 0.2607 | |
| | 0.2993 | 660 | 0.4991 | - | - | |
| | 0.3084 | 680 | 0.5034 | - | - | |
| | 0.3175 | 700 | 0.4655 | - | - | |
| | 0.3265 | 720 | 0.5191 | 0.5107 | 0.2969 | |
| | 0.3356 | 740 | 0.509 | - | - | |
| | 0.3447 | 760 | 0.484 | - | - | |
| | 0.3537 | 780 | 0.5113 | - | - | |
| | 0.3628 | 800 | 0.4968 | 0.4966 | 0.3645 | |
| | 0.3719 | 820 | 0.4713 | - | - | |
| | 0.3810 | 840 | 0.507 | - | - | |
| | 0.3900 | 860 | 0.5041 | - | - | |
| | 0.3991 | 880 | 0.4868 | 0.4953 | 0.3896 | |
| | 0.4082 | 900 | 0.4985 | - | - | |
| | 0.4172 | 920 | 0.477 | - | - | |
| | 0.4263 | 940 | 0.4888 | - | - | |
| | 0.4354 | 960 | 0.4791 | 0.4916 | 0.4280 | |
| | 0.4444 | 980 | 0.4969 | - | - | |
| | 0.4535 | 1000 | 0.4757 | - | - | |
| | 0.4626 | 1020 | 0.4978 | - | - | |
| | 0.4717 | 1040 | 0.4998 | 0.4966 | 0.4299 | |
| | 0.4807 | 1060 | 0.5062 | - | - | |
| | 0.4898 | 1080 | 0.4876 | - | - | |
| | 0.4989 | 1100 | 0.4836 | - | - | |
| | 0.5079 | 1120 | 0.5034 | 0.4908 | 0.4404 | |
| | 0.5170 | 1140 | 0.4788 | - | - | |
| | 0.5261 | 1160 | 0.5037 | - | - | |
| | 0.5351 | 1180 | 0.467 | - | - | |
| | 0.5442 | 1200 | 0.4785 | 0.4942 | 0.4701 | |
| | 0.5533 | 1220 | 0.502 | - | - | |
| | 0.5624 | 1240 | 0.5223 | - | - | |
| | 0.5714 | 1260 | 0.4755 | - | - | |
| | 0.5805 | 1280 | 0.4826 | 0.4888 | 0.4685 | |
| | 0.5896 | 1300 | 0.493 | - | - | |
| | 0.5986 | 1320 | 0.4935 | - | - | |
| | 0.6077 | 1340 | 0.4851 | - | - | |
| | 0.6168 | 1360 | 0.4884 | 0.4908 | 0.5028 | |
| | 0.6259 | 1380 | 0.4966 | - | - | |
| | 0.6349 | 1400 | 0.4769 | - | - | |
| | 0.6440 | 1420 | 0.4965 | - | - | |
| | 0.6531 | 1440 | 0.492 | 0.4869 | 0.5234 | |
| | 0.6621 | 1460 | 0.487 | - | - | |
| | 0.6712 | 1480 | 0.5045 | - | - | |
| | 0.6803 | 1500 | 0.4638 | - | - | |
| | 0.6893 | 1520 | 0.4622 | 0.4874 | 0.5281 | |
| | 0.6984 | 1540 | 0.468 | - | - | |
| | 0.7075 | 1560 | 0.4627 | - | - | |
| | 0.7166 | 1580 | 0.4892 | - | - | |
| | 0.7256 | 1600 | 0.5044 | 0.4885 | 0.5219 | |
| | 0.7347 | 1620 | 0.4941 | - | - | |
| | 0.7438 | 1640 | 0.4857 | - | - | |
| | 0.7528 | 1660 | 0.497 | - | - | |
| | 0.7619 | 1680 | 0.5007 | 0.4925 | 0.5146 | |
| | 0.7710 | 1700 | 0.5038 | - | - | |
| | 0.7800 | 1720 | 0.4702 | - | - | |
| | 0.7891 | 1740 | 0.4754 | - | - | |
| | 0.7982 | 1760 | 0.4852 | 0.4874 | 0.5402 | |
| | 0.8073 | 1780 | 0.4858 | - | - | |
| | 0.8163 | 1800 | 0.493 | - | - | |
| | 0.8254 | 1820 | 0.4802 | - | - | |
| | 0.8345 | 1840 | 0.4905 | 0.4865 | 0.5370 | |
| | 0.8435 | 1860 | 0.5 | - | - | |
| | 0.8526 | 1880 | 0.4888 | - | - | |
| | 0.8617 | 1900 | 0.4764 | - | - | |
| | 0.8707 | 1920 | 0.4647 | 0.4885 | 0.5100 | |
| | 0.8798 | 1940 | 0.4714 | - | - | |
| | 0.8889 | 1960 | 0.497 | - | - | |
| | 0.8980 | 1980 | 0.4878 | - | - | |
| | 0.9070 | 2000 | 0.4906 | 0.4855 | 0.5633 | |
| | 0.9161 | 2020 | 0.5018 | - | - | |
| | 0.9252 | 2040 | 0.4998 | - | - | |
| | 0.9342 | 2060 | 0.4619 | - | - | |
| | 0.9433 | 2080 | 0.4722 | 0.4855 | 0.5575 | |
| | 0.9524 | 2100 | 0.487 | - | - | |
| | 0.9615 | 2120 | 0.4798 | - | - | |
| | 0.9705 | 2140 | 0.46 | - | - | |
| | 0.9796 | 2160 | 0.4683 | 0.4844 | 0.5710 | |
| | 0.9887 | 2180 | 0.5026 | - | - | |
| | 0.9977 | 2200 | 0.4905 | - | - | |
| | 1.0068 | 2220 | 0.5008 | - | - | |
| | 1.0159 | 2240 | 0.4918 | 0.4832 | 0.5951 | |
| | 1.0249 | 2260 | 0.4809 | - | - | |
| | 1.0340 | 2280 | 0.4964 | - | - | |
| | 1.0431 | 2300 | 0.4562 | - | - | |
| | 1.0522 | 2320 | 0.4529 | 0.4862 | 0.5884 | |
| | 1.0612 | 2340 | 0.4689 | - | - | |
| | 1.0703 | 2360 | 0.4811 | - | - | |
| | 1.0794 | 2380 | 0.4822 | - | - | |
| | 1.0884 | 2400 | 0.4944 | 0.4832 | 0.5892 | |
| | 1.0975 | 2420 | 0.5001 | - | - | |
| | 1.1066 | 2440 | 0.4912 | - | - | |
| | 1.1156 | 2460 | 0.4826 | - | - | |
| | 1.1247 | 2480 | 0.47 | 0.4834 | 0.5988 | |
| | 1.1338 | 2500 | 0.4818 | - | - | |
| | 1.1429 | 2520 | 0.4648 | - | - | |
| | 1.1519 | 2540 | 0.4687 | - | - | |
| | 1.1610 | 2560 | 0.4737 | 0.4837 | 0.5984 | |
| | 1.1701 | 2580 | 0.4789 | - | - | |
| | 1.1791 | 2600 | 0.4876 | - | - | |
| | 1.1882 | 2620 | 0.4952 | - | - | |
| | 1.1973 | 2640 | 0.4861 | 0.4823 | 0.5981 | |
| | 1.2063 | 2660 | 0.4758 | - | - | |
| | 1.2154 | 2680 | 0.4927 | - | - | |
| | 1.2245 | 2700 | 0.4897 | - | - | |
| | 1.2336 | 2720 | 0.4785 | 0.4835 | 0.6037 | |
| | 1.2426 | 2740 | 0.5027 | - | - | |
| | 1.2517 | 2760 | 0.4776 | - | - | |
| | 1.2608 | 2780 | 0.445 | - | - | |
| | 1.2698 | 2800 | 0.4675 | 0.4844 | 0.6264 | |
| | 1.2789 | 2820 | 0.4646 | - | - | |
| | 1.2880 | 2840 | 0.4822 | - | - | |
| | 1.2971 | 2860 | 0.4669 | - | - | |
| | 1.3061 | 2880 | 0.4817 | 0.4823 | 0.6375 | |
| | 1.3152 | 2900 | 0.4759 | - | - | |
| | 1.3243 | 2920 | 0.4876 | - | - | |
| | 1.3333 | 2940 | 0.4689 | - | - | |
| | 1.3424 | 2960 | 0.4751 | 0.4807 | 0.6520 | |
| | 1.3515 | 2980 | 0.4872 | - | - | |
| | 1.3605 | 3000 | 0.4543 | - | - | |
| | 1.3696 | 3020 | 0.4687 | - | - | |
| | 1.3787 | 3040 | 0.4759 | 0.4819 | 0.6136 | |
| | 1.3878 | 3060 | 0.4827 | - | - | |
| | 1.3968 | 3080 | 0.4876 | - | - | |
| | 1.4059 | 3100 | 0.4791 | - | - | |
| | 1.4150 | 3120 | 0.4887 | 0.4818 | 0.6314 | |
| | 1.4240 | 3140 | 0.4863 | - | - | |
| | 1.4331 | 3160 | 0.4864 | - | - | |
| | 1.4422 | 3180 | 0.4824 | - | - | |
| | 1.4512 | 3200 | 0.4974 | 0.4829 | 0.6645 | |
| | 1.4603 | 3220 | 0.4554 | - | - | |
| | 1.4694 | 3240 | 0.484 | - | - | |
| | 1.4785 | 3260 | 0.4735 | - | - | |
| | 1.4875 | 3280 | 0.504 | 0.4832 | 0.6617 | |
| | 1.4966 | 3300 | 0.4758 | - | - | |
| | 1.5057 | 3320 | 0.4711 | - | - | |
| | 1.5147 | 3340 | 0.486 | - | - | |
| | 1.5238 | 3360 | 0.4751 | 0.4815 | 0.6502 | |
| | 1.5329 | 3380 | 0.4761 | - | - | |
| | 1.5420 | 3400 | 0.467 | - | - | |
| | 1.5510 | 3420 | 0.4706 | - | - | |
| | 1.5601 | 3440 | 0.4894 | 0.4798 | 0.6549 | |
| | 1.5692 | 3460 | 0.4795 | - | - | |
| | 1.5782 | 3480 | 0.4922 | - | - | |
| | 1.5873 | 3500 | 0.4763 | - | - | |
| | 1.5964 | 3520 | 0.4801 | 0.4804 | 0.6608 | |
| | 1.6054 | 3540 | 0.4692 | - | - | |
| | 1.6145 | 3560 | 0.4886 | - | - | |
| | 1.6236 | 3580 | 0.4758 | - | - | |
| | 1.6327 | 3600 | 0.456 | 0.4801 | 0.6651 | |
| | 1.6417 | 3620 | 0.496 | - | - | |
| | 1.6508 | 3640 | 0.5179 | - | - | |
| | 1.6599 | 3660 | 0.4729 | - | - | |
| | 1.6689 | 3680 | 0.4612 | 0.4785 | 0.6767 | |
| | 1.6780 | 3700 | 0.4628 | - | - | |
| | 1.6871 | 3720 | 0.4516 | - | - | |
| | 1.6961 | 3740 | 0.4773 | - | - | |
| | 1.7052 | 3760 | 0.4732 | 0.4781 | 0.6798 | |
| | 1.7143 | 3780 | 0.5025 | - | - | |
| | 1.7234 | 3800 | 0.4843 | - | - | |
| | 1.7324 | 3820 | 0.4799 | - | - | |
| | 1.7415 | 3840 | 0.4753 | 0.4781 | 0.6837 | |
| | 1.7506 | 3860 | 0.4568 | - | - | |
| | 1.7596 | 3880 | 0.4782 | - | - | |
| | 1.7687 | 3900 | 0.4855 | - | - | |
| | 1.7778 | 3920 | 0.4699 | 0.4791 | 0.6913 | |
| | 1.7868 | 3940 | 0.48 | - | - | |
| | 1.7959 | 3960 | 0.4743 | - | - | |
| | 1.8050 | 3980 | 0.453 | - | - | |
| | 1.8141 | 4000 | 0.4755 | 0.4816 | 0.6937 | |
| | 1.8231 | 4020 | 0.4419 | - | - | |
| | 1.8322 | 4040 | 0.4724 | - | - | |
| | 1.8413 | 4060 | 0.4892 | - | - | |
| | 1.8503 | 4080 | 0.4779 | 0.4829 | 0.6903 | |
| | 1.8594 | 4100 | 0.4748 | - | - | |
| | 1.8685 | 4120 | 0.4909 | - | - | |
| | 1.8776 | 4140 | 0.5026 | - | - | |
| | 1.8866 | 4160 | 0.4668 | 0.4795 | 0.7060 | |
| | 1.8957 | 4180 | 0.47 | - | - | |
| | 1.9048 | 4200 | 0.4977 | - | - | |
| | 1.9138 | 4220 | 0.4644 | - | - | |
| | 1.9229 | 4240 | 0.4745 | 0.4777 | 0.7053 | |
| | 1.9320 | 4260 | 0.455 | - | - | |
| | 1.9410 | 4280 | 0.4864 | - | - | |
| | 1.9501 | 4300 | 0.4987 | - | - | |
| | 1.9592 | 4320 | 0.4716 | 0.4770 | 0.6948 | |
| | 1.9683 | 4340 | 0.4877 | - | - | |
| | 1.9773 | 4360 | 0.4741 | - | - | |
| | 1.9864 | 4380 | 0.4969 | - | - | |
| | 1.9955 | 4400 | 0.4733 | 0.4767 | 0.7052 | |
| | 2.0045 | 4420 | 0.4842 | - | - | |
| | 2.0136 | 4440 | 0.48 | - | - | |
| | 2.0227 | 4460 | 0.4985 | - | - | |
| | 2.0317 | 4480 | 0.483 | 0.4760 | 0.7110 | |
| | 2.0408 | 4500 | 0.482 | - | - | |
| | 2.0499 | 4520 | 0.4687 | - | - | |
| | 2.0590 | 4540 | 0.4595 | - | - | |
| | 2.0680 | 4560 | 0.4699 | 0.4764 | 0.7095 | |
| | 2.0771 | 4580 | 0.4426 | - | - | |
| | 2.0862 | 4600 | 0.4691 | - | - | |
| | 2.0952 | 4620 | 0.4568 | - | - | |
| | 2.1043 | 4640 | 0.4716 | 0.4774 | 0.7124 | |
| | 2.1134 | 4660 | 0.4696 | - | - | |
| | 2.1224 | 4680 | 0.4737 | - | - | |
| | 2.1315 | 4700 | 0.4925 | - | - | |
| | 2.1406 | 4720 | 0.4708 | 0.4754 | 0.7274 | |
| | 2.1497 | 4740 | 0.4531 | - | - | |
| | 2.1587 | 4760 | 0.473 | - | - | |
| | 2.1678 | 4780 | 0.4824 | - | - | |
| | 2.1769 | 4800 | 0.4573 | 0.4760 | 0.7291 | |
| | 2.1859 | 4820 | 0.4774 | - | - | |
| | 2.1950 | 4840 | 0.4776 | - | - | |
| | 2.2041 | 4860 | 0.4764 | - | - | |
| | 2.2132 | 4880 | 0.4893 | 0.4749 | 0.7352 | |
| | 2.2222 | 4900 | 0.4793 | - | - | |
| | 2.2313 | 4920 | 0.4473 | - | - | |
| | 2.2404 | 4940 | 0.4851 | - | - | |
| | 2.2494 | 4960 | 0.4787 | 0.4757 | 0.7261 | |
| | 2.2585 | 4980 | 0.4676 | - | - | |
| | 2.2676 | 5000 | 0.4621 | - | - | |
| | 2.2766 | 5020 | 0.4714 | - | - | |
| | 2.2857 | 5040 | 0.4758 | 0.4762 | 0.7230 | |
| | 2.2948 | 5060 | 0.4754 | - | - | |
| | 2.3039 | 5080 | 0.4305 | - | - | |
| | 2.3129 | 5100 | 0.4752 | - | - | |
| | 2.3220 | 5120 | 0.4606 | 0.4759 | 0.7355 | |
| | 2.3311 | 5140 | 0.4936 | - | - | |
| | 2.3401 | 5160 | 0.4456 | - | - | |
| | 2.3492 | 5180 | 0.489 | - | - | |
| | 2.3583 | 5200 | 0.4633 | 0.4779 | 0.7319 | |
| | 2.3673 | 5220 | 0.4909 | - | - | |
| | 2.3764 | 5240 | 0.4601 | - | - | |
| | 2.3855 | 5260 | 0.476 | - | - | |
| | 2.3946 | 5280 | 0.4793 | 0.4739 | 0.7454 | |
| | 2.4036 | 5300 | 0.4618 | - | - | |
| | 2.4127 | 5320 | 0.4668 | - | - | |
| | 2.4218 | 5340 | 0.4621 | - | - | |
| | 2.4308 | 5360 | 0.4732 | 0.4749 | 0.7412 | |
| | 2.4399 | 5380 | 0.4683 | - | - | |
| | 2.4490 | 5400 | 0.4902 | - | - | |
| | 2.4580 | 5420 | 0.4629 | - | - | |
| | 2.4671 | 5440 | 0.4917 | 0.4748 | 0.7353 | |
| | 2.4762 | 5460 | 0.4783 | - | - | |
| | 2.4853 | 5480 | 0.4865 | - | - | |
| | 2.4943 | 5500 | 0.4838 | - | - | |
| | 2.5034 | 5520 | 0.4486 | 0.4759 | 0.7376 | |
| | 2.5125 | 5540 | 0.4705 | - | - | |
| | 2.5215 | 5560 | 0.4713 | - | - | |
| | 2.5306 | 5580 | 0.5 | - | - | |
| | 2.5397 | 5600 | 0.4645 | 0.4753 | 0.7415 | |
| | 2.5488 | 5620 | 0.4655 | - | - | |
| | 2.5578 | 5640 | 0.4646 | - | - | |
| | 2.5669 | 5660 | 0.4608 | - | - | |
| | 2.5760 | 5680 | 0.4752 | 0.4741 | 0.7406 | |
| | 2.5850 | 5700 | 0.4608 | - | - | |
| | 2.5941 | 5720 | 0.46 | - | - | |
| | 2.6032 | 5740 | 0.4603 | - | - | |
| | 2.6122 | 5760 | 0.4686 | 0.4734 | 0.7438 | |
| | 2.6213 | 5780 | 0.4542 | - | - | |
| | 2.6304 | 5800 | 0.4718 | - | - | |
| | 2.6395 | 5820 | 0.4615 | - | - | |
| | 2.6485 | 5840 | 0.4749 | 0.4729 | 0.7552 | |
| | 2.6576 | 5860 | 0.4951 | - | - | |
| | 2.6667 | 5880 | 0.4944 | - | - | |
| | 2.6757 | 5900 | 0.459 | - | - | |
| | 2.6848 | 5920 | 0.4593 | 0.4743 | 0.7567 | |
| | 2.6939 | 5940 | 0.474 | - | - | |
| | 2.7029 | 5960 | 0.4555 | - | - | |
| | 2.7120 | 5980 | 0.465 | - | - | |
| | 2.7211 | 6000 | 0.4583 | 0.4730 | 0.7560 | |
| | 2.7302 | 6020 | 0.4528 | - | - | |
| | 2.7392 | 6040 | 0.4375 | - | - | |
| | 2.7483 | 6060 | 0.4838 | - | - | |
| | 2.7574 | 6080 | 0.4995 | 0.4729 | 0.7552 | |
| | 2.7664 | 6100 | 0.4687 | - | - | |
| | 2.7755 | 6120 | 0.4615 | - | - | |
| | 2.7846 | 6140 | 0.4619 | - | - | |
| | 2.7937 | 6160 | 0.4726 | 0.4734 | 0.7589 | |
| | 2.8027 | 6180 | 0.4699 | - | - | |
| | 2.8118 | 6200 | 0.4772 | - | - | |
| | 2.8209 | 6220 | 0.469 | - | - | |
| | 2.8299 | 6240 | 0.4592 | 0.4728 | 0.7640 | |
| | 2.8390 | 6260 | 0.4599 | - | - | |
| | 2.8481 | 6280 | 0.4642 | - | - | |
| | 2.8571 | 6300 | 0.4658 | - | - | |
| | 2.8662 | 6320 | 0.4786 | 0.4724 | 0.7655 | |
| | 2.8753 | 6340 | 0.4537 | - | - | |
| | 2.8844 | 6360 | 0.4984 | - | - | |
| | 2.8934 | 6380 | 0.4816 | - | - | |
| | 2.9025 | 6400 | 0.4598 | 0.4726 | 0.7649 | |
| | 2.9116 | 6420 | 0.4775 | - | - | |
| | 2.9206 | 6440 | 0.4802 | - | - | |
| | 2.9297 | 6460 | 0.4556 | - | - | |
| | 2.9388 | 6480 | 0.4787 | 0.4744 | 0.7737 | |
| | 2.9478 | 6500 | 0.4835 | - | - | |
| | 2.9569 | 6520 | 0.4638 | - | - | |
| | 2.9660 | 6540 | 0.4912 | - | - | |
| | 2.9751 | 6560 | 0.4727 | 0.4718 | 0.7725 | |
| | 2.9841 | 6580 | 0.4637 | - | - | |
| | 2.9932 | 6600 | 0.4934 | - | - | |
| | 3.0023 | 6620 | 0.4632 | - | - | |
| | 3.0113 | 6640 | 0.4772 | 0.4720 | 0.7786 | |
| | 3.0204 | 6660 | 0.4565 | - | - | |
| | 3.0295 | 6680 | 0.4433 | - | - | |
| | 3.0385 | 6700 | 0.4642 | - | - | |
| | 3.0476 | 6720 | 0.4603 | 0.4737 | 0.7768 | |
| | 3.0567 | 6740 | 0.466 | - | - | |
| | 3.0658 | 6760 | 0.4509 | - | - | |
| | 3.0748 | 6780 | 0.4455 | - | - | |
| | 3.0839 | 6800 | 0.4808 | 0.4718 | 0.7777 | |
| | 3.0930 | 6820 | 0.4836 | - | - | |
| | 3.1020 | 6840 | 0.4823 | - | - | |
| | 3.1111 | 6860 | 0.469 | - | - | |
| | 3.1202 | 6880 | 0.4654 | 0.4715 | 0.7777 | |
| | 3.1293 | 6900 | 0.4705 | - | - | |
| | 3.1383 | 6920 | 0.4869 | - | - | |
| | 3.1474 | 6940 | 0.4964 | - | - | |
| | 3.1565 | 6960 | 0.4346 | 0.4729 | 0.7823 | |
| | 3.1655 | 6980 | 0.478 | - | - | |
| | 3.1746 | 7000 | 0.4691 | - | - | |
| | 3.1837 | 7020 | 0.45 | - | - | |
| | 3.1927 | 7040 | 0.4821 | 0.4715 | 0.7868 | |
| | 3.2018 | 7060 | 0.4652 | - | - | |
| | 3.2109 | 7080 | 0.4654 | - | - | |
| | 3.2200 | 7100 | 0.4561 | - | - | |
| | 3.2290 | 7120 | 0.4657 | 0.4713 | 0.7860 | |
| | 3.2381 | 7140 | 0.4431 | - | - | |
| | 3.2472 | 7160 | 0.448 | - | - | |
| | 3.2562 | 7180 | 0.478 | - | - | |
| | 3.2653 | 7200 | 0.4574 | 0.4707 | 0.7913 | |
| | 3.2744 | 7220 | 0.4589 | - | - | |
| | 3.2834 | 7240 | 0.4759 | - | - | |
| | 3.2925 | 7260 | 0.4703 | - | - | |
| | 3.3016 | 7280 | 0.4683 | 0.4712 | 0.7943 | |
| | 3.3107 | 7300 | 0.4576 | - | - | |
| | 3.3197 | 7320 | 0.4517 | - | - | |
| | 3.3288 | 7340 | 0.4498 | - | - | |
| | 3.3379 | 7360 | 0.4782 | 0.4705 | 0.7961 | |
| | 3.3469 | 7380 | 0.476 | - | - | |
| | 3.3560 | 7400 | 0.4642 | - | - | |
| | 3.3651 | 7420 | 0.4923 | - | - | |
| | 3.3741 | 7440 | 0.4637 | 0.4706 | 0.7949 | |
| | 3.3832 | 7460 | 0.4512 | - | - | |
| | 3.3923 | 7480 | 0.4392 | - | - | |
| | 3.4014 | 7500 | 0.486 | - | - | |
| | 3.4104 | 7520 | 0.4632 | 0.4709 | 0.7950 | |
| | 3.4195 | 7540 | 0.4816 | - | - | |
| | 3.4286 | 7560 | 0.46 | - | - | |
| | 3.4376 | 7580 | 0.473 | - | - | |
| | 3.4467 | 7600 | 0.4618 | 0.4708 | 0.7953 | |
| | 3.4558 | 7620 | 0.4584 | - | - | |
| | 3.4649 | 7640 | 0.46 | - | - | |
| | 3.4739 | 7660 | 0.4655 | - | - | |
| | 3.4830 | 7680 | 0.4461 | 0.4713 | 0.7981 | |
| | 3.4921 | 7700 | 0.4521 | - | - | |
| | 3.5011 | 7720 | 0.4802 | - | - | |
| | 3.5102 | 7740 | 0.464 | - | - | |
| | 3.5193 | 7760 | 0.481 | 0.4699 | 0.7991 | |
| | 3.5283 | 7780 | 0.4719 | - | - | |
| | 3.5374 | 7800 | 0.4615 | - | - | |
| | 3.5465 | 7820 | 0.458 | - | - | |
| | 3.5556 | 7840 | 0.4659 | 0.4700 | 0.7996 | |
| | 3.5646 | 7860 | 0.4688 | - | - | |
| | 3.5737 | 7880 | 0.457 | - | - | |
| | 3.5828 | 7900 | 0.4821 | - | - | |
| | 3.5918 | 7920 | 0.4567 | 0.4707 | 0.8018 | |
| | 3.6009 | 7940 | 0.4722 | - | - | |
| | 3.6100 | 7960 | 0.4785 | - | - | |
| | 3.6190 | 7980 | 0.4904 | - | - | |
| | 3.6281 | 8000 | 0.483 | 0.4698 | 0.8012 | |
| | 3.6372 | 8020 | 0.4756 | - | - | |
| | 3.6463 | 8040 | 0.4689 | - | - | |
| | 3.6553 | 8060 | 0.4774 | - | - | |
| | 3.6644 | 8080 | 0.4638 | 0.4707 | 0.8015 | |
| | 3.6735 | 8100 | 0.4648 | - | - | |
| | 3.6825 | 8120 | 0.478 | - | - | |
| | 3.6916 | 8140 | 0.4839 | - | - | |
| | 3.7007 | 8160 | 0.4623 | 0.4696 | 0.8036 | |
| | 3.7098 | 8180 | 0.4558 | - | - | |
| | 3.7188 | 8200 | 0.4575 | - | - | |
| | 3.7279 | 8220 | 0.4628 | - | - | |
| | 3.7370 | 8240 | 0.4552 | 0.4702 | 0.8042 | |
| | 3.7460 | 8260 | 0.4655 | - | - | |
| | 3.7551 | 8280 | 0.4687 | - | - | |
| | 3.7642 | 8300 | 0.4549 | - | - | |
| | 3.7732 | 8320 | 0.4522 | 0.4700 | 0.8052 | |
| | 3.7823 | 8340 | 0.4424 | - | - | |
| | 3.7914 | 8360 | 0.4612 | - | - | |
| | 3.8005 | 8380 | 0.4606 | - | - | |
| | 3.8095 | 8400 | 0.4553 | 0.4695 | 0.8058 | |
| | 3.8186 | 8420 | 0.4661 | - | - | |
| | 3.8277 | 8440 | 0.4811 | - | - | |
| | 3.8367 | 8460 | 0.4661 | - | - | |
| | 3.8458 | 8480 | 0.4805 | 0.4695 | 0.8065 | |
| | 3.8549 | 8500 | 0.4761 | - | - | |
| | 3.8639 | 8520 | 0.4778 | - | - | |
| | 3.8730 | 8540 | 0.4566 | - | - | |
| | 3.8821 | 8560 | 0.4359 | 0.4695 | 0.8067 | |
| | 3.8912 | 8580 | 0.47 | - | - | |
| | 3.9002 | 8600 | 0.4851 | - | - | |
| | 3.9093 | 8620 | 0.4609 | - | - | |
| | 3.9184 | 8640 | 0.4675 | 0.4695 | 0.8068 | |
| | 3.9274 | 8660 | 0.4628 | - | - | |
| | 3.9365 | 8680 | 0.4604 | - | - | |
| | 3.9456 | 8700 | 0.4829 | - | - | |
| | 3.9546 | 8720 | 0.462 | 0.4695 | 0.8071 | |
| | 3.9637 | 8740 | 0.4554 | - | - | |
| | 3.9728 | 8760 | 0.4674 | - | - | |
| | 3.9819 | 8780 | 0.4721 | - | - | |
| | 3.9909 | 8800 | 0.4534 | 0.4695 | 0.8073 | |
| | 4.0 | 8820 | 0.4667 | - | - | |
| | -1 | -1 | - | - | 0.7876 | |
| |
| </details> |
| |
| ### Framework Versions |
| - Python: 3.11.12 |
| - Sentence Transformers: 4.1.0 |
| - Transformers: 4.51.3 |
| - PyTorch: 2.6.0+cu124 |
| - Accelerate: 1.5.2 |
| - Datasets: 3.5.0 |
| - Tokenizers: 0.21.1 |
| |
| ## 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", |
| } |
| ``` |
| |
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