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---
base_model: Alibaba-NLP/gte-base-en-v1.5
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- dataset_size:1K<n<10K
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: Żywot św. Stanisława
sentences:
- czym różni się Żywot św. Stanisława od Legendy św. Stanisława?
- Mistrzostwa Krajów Bałkańskich w Lekkoatletyce 2012
- dlaczego współcześni perfumiarze rzadko stosują zapach lawendy?
- source_sentence: Bitwa nad Stones River
sentences:
- czyim zwycięstwem zakończyła się bitwa nad Stones River?
- w jakim kraju jest przyznawany Order Białego Lotosu?
- kiedy Victor Horta otrzymał tytuł barona?
- source_sentence: gdzie rośnie bokkonia?
sentences:
- gdzie występuje rogownica szerokolistna?
- ile goli dla Slawii Sofia strzelił Władimir Iwanow?
- Przewody płciowe męskie i żeńskie uchodzą u nich odrębnymi otworami.
- source_sentence: czym jest Kompas Sztuki?
sentences:
- ' Projekt Kompas Sztuki: Galeria m2 (m kwadrat).'
- 'Do rodzaju Caraipa zaliczanych jest ok. 55 gatunków:'
- w którym mieście działał malarz renesansowy Jacobello del Fiore?
- source_sentence: Sen o zastrzyku Irmy
sentences:
- gdzie Freud spotkał Irmę we śnie o zastrzyku Irmy?
- ile razy Srebrna Biblia była przywożona do Szwecji?
- jaką techniką został namalowany obraz Bruegela Chrystus i cudzołożnica?
model-index:
- name: gte-base-en-v1.5-klej-dyk-v0.1
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 768
type: dim_768
metrics:
- type: cosine_accuracy@1
value: 0.20673076923076922
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.4855769230769231
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.6730769230769231
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.7908653846153846
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.20673076923076922
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.16185897435897434
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.1346153846153846
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.07908653846153846
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.20673076923076922
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.4855769230769231
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.6730769230769231
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.7908653846153846
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.48188411689532745
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.3839848519536019
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.3897833313631923
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 512
type: dim_512
metrics:
- type: cosine_accuracy@1
value: 0.19471153846153846
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.47596153846153844
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.6586538461538461
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.7716346153846154
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.19471153846153846
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.15865384615384615
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.13173076923076923
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.07716346153846153
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.19471153846153846
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.47596153846153844
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.6586538461538461
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.7716346153846154
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.4699784661922609
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.3740689865689866
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.3807931969694512
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 256
type: dim_256
metrics:
- type: cosine_accuracy@1
value: 0.19471153846153846
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.4639423076923077
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.6466346153846154
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.7307692307692307
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.19471153846153846
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.15464743589743588
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.12932692307692306
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.07307692307692307
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.19471153846153846
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.4639423076923077
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.6466346153846154
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.7307692307692307
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.4534215890186354
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.36472355769230763
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.3730539351737456
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 128
type: dim_128
metrics:
- type: cosine_accuracy@1
value: 0.19471153846153846
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.42788461538461536
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.5721153846153846
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.6899038461538461
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.19471153846153846
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.14262820512820512
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.1144230769230769
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.0689903846153846
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.19471153846153846
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.42788461538461536
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.5721153846153846
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.6899038461538461
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.42667299025011857
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.3438606532356531
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.3517227578608955
name: Cosine Map@100
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 64
type: dim_64
metrics:
- type: cosine_accuracy@1
value: 0.1778846153846154
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.3701923076923077
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.45913461538461536
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.5793269230769231
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.1778846153846154
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.12339743589743589
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.09182692307692308
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.05793269230769231
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.1778846153846154
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.3701923076923077
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.45913461538461536
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.5793269230769231
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.3628128840276353
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.29511885683760675
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.3068359520768717
name: Cosine Map@100
---
# gte-base-en-v1.5-klej-dyk-v0.1
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-base-en-v1.5](https://huggingface.co./Alibaba-NLP/gte-base-en-v1.5). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [Alibaba-NLP/gte-base-en-v1.5](https://huggingface.co./Alibaba-NLP/gte-base-en-v1.5) <!-- at revision 269b9aca14a582d83e31b8c76b2e85a266fc1d77 -->
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
- **Language:** en
- **License:** apache-2.0
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co./models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: NewModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
'Sen o zastrzyku Irmy',
'gdzie Freud spotkał Irmę we śnie o zastrzyku Irmy?',
'ile razy Srebrna Biblia była przywożona do Szwecji?',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `dim_768`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.2067 |
| cosine_accuracy@3 | 0.4856 |
| cosine_accuracy@5 | 0.6731 |
| cosine_accuracy@10 | 0.7909 |
| cosine_precision@1 | 0.2067 |
| cosine_precision@3 | 0.1619 |
| cosine_precision@5 | 0.1346 |
| cosine_precision@10 | 0.0791 |
| cosine_recall@1 | 0.2067 |
| cosine_recall@3 | 0.4856 |
| cosine_recall@5 | 0.6731 |
| cosine_recall@10 | 0.7909 |
| cosine_ndcg@10 | 0.4819 |
| cosine_mrr@10 | 0.384 |
| **cosine_map@100** | **0.3898** |
#### Information Retrieval
* Dataset: `dim_512`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.1947 |
| cosine_accuracy@3 | 0.476 |
| cosine_accuracy@5 | 0.6587 |
| cosine_accuracy@10 | 0.7716 |
| cosine_precision@1 | 0.1947 |
| cosine_precision@3 | 0.1587 |
| cosine_precision@5 | 0.1317 |
| cosine_precision@10 | 0.0772 |
| cosine_recall@1 | 0.1947 |
| cosine_recall@3 | 0.476 |
| cosine_recall@5 | 0.6587 |
| cosine_recall@10 | 0.7716 |
| cosine_ndcg@10 | 0.47 |
| cosine_mrr@10 | 0.3741 |
| **cosine_map@100** | **0.3808** |
#### Information Retrieval
* Dataset: `dim_256`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.1947 |
| cosine_accuracy@3 | 0.4639 |
| cosine_accuracy@5 | 0.6466 |
| cosine_accuracy@10 | 0.7308 |
| cosine_precision@1 | 0.1947 |
| cosine_precision@3 | 0.1546 |
| cosine_precision@5 | 0.1293 |
| cosine_precision@10 | 0.0731 |
| cosine_recall@1 | 0.1947 |
| cosine_recall@3 | 0.4639 |
| cosine_recall@5 | 0.6466 |
| cosine_recall@10 | 0.7308 |
| cosine_ndcg@10 | 0.4534 |
| cosine_mrr@10 | 0.3647 |
| **cosine_map@100** | **0.3731** |
#### Information Retrieval
* Dataset: `dim_128`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.1947 |
| cosine_accuracy@3 | 0.4279 |
| cosine_accuracy@5 | 0.5721 |
| cosine_accuracy@10 | 0.6899 |
| cosine_precision@1 | 0.1947 |
| cosine_precision@3 | 0.1426 |
| cosine_precision@5 | 0.1144 |
| cosine_precision@10 | 0.069 |
| cosine_recall@1 | 0.1947 |
| cosine_recall@3 | 0.4279 |
| cosine_recall@5 | 0.5721 |
| cosine_recall@10 | 0.6899 |
| cosine_ndcg@10 | 0.4267 |
| cosine_mrr@10 | 0.3439 |
| **cosine_map@100** | **0.3517** |
#### Information Retrieval
* Dataset: `dim_64`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.1779 |
| cosine_accuracy@3 | 0.3702 |
| cosine_accuracy@5 | 0.4591 |
| cosine_accuracy@10 | 0.5793 |
| cosine_precision@1 | 0.1779 |
| cosine_precision@3 | 0.1234 |
| cosine_precision@5 | 0.0918 |
| cosine_precision@10 | 0.0579 |
| cosine_recall@1 | 0.1779 |
| cosine_recall@3 | 0.3702 |
| cosine_recall@5 | 0.4591 |
| cosine_recall@10 | 0.5793 |
| cosine_ndcg@10 | 0.3628 |
| cosine_mrr@10 | 0.2951 |
| **cosine_map@100** | **0.3068** |
<!--
## 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: 3,738 training samples
* Columns: <code>positive</code> and <code>anchor</code>
* Approximate statistics based on the first 1000 samples:
| | positive | anchor |
|:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 7 tokens</li><li>mean: 89.43 tokens</li><li>max: 507 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 30.98 tokens</li><li>max: 76 tokens</li></ul> |
* Samples:
| positive | anchor |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------|
| <code>Zespół Blaua (zespół Jabsa, ang. Blau syndrome, BS) – rzadka choroba genetyczna o dziedziczeniu autosomalnym dominującym, charakteryzująca się ziarniniakowym zapaleniem stawów o wczesnym początku, zapaleniem jagodówki (uveitis) i wysypką skórną, a także kamptodaktylią.</code> | <code>jakie choroby genetyczne dziedziczą się autosomalnie dominująco?</code> |
| <code>Gorgippia Gorgippia – starożytne miasto bosporańskie nad Morzem Czarnym, którego pozostałości znajdują się obecnie pod współczesną zabudową centralnej części miasta Anapa w Kraju Krasnodarskim w Rosji.</code> | <code>gdzie obecnie znajduje się starożytne miasto Gorgippia?</code> |
| <code>Ulubionym dystansem Rücker było 400 metrów i to na nim notowała największe indywidualne sukcesy : srebrny medal Mistrzostw Europy juniorów w lekkoatletyce (Saloniki 1991) 6. miejsce w Pucharze Świata w Lekkoatletyce (Hawana 1992) 5. miejsce na Mistrzostwach Europy w Lekkoatletyce (Helsinki 1994) srebro podczas Mistrzostw Świata w Lekkoatletyce (Sewilla 1999) złota medalistka mistrzostw Niemiec Duże sukcesy odnosiła także w sztafecie 4 x 400 metrów : złoto Mistrzostw Europy juniorów w lekkoatletyce (Varaždin 1989) złoty medal Mistrzostw Europy juniorów w lekkoatletyce (Saloniki 1991) brąz na Mistrzostwach Europy w Lekkoatletyce (Helsinki 1994) brązowy medal podczas Igrzysk Olimpijskich (Atlanta 1996) brąz na Halowych Mistrzostwach Świata w Lekkoatletyce (Paryż 1997) złoto Mistrzostw Świata w Lekkoatletyce (Ateny 1997) brązowy medal Mistrzostw Świata w Lekkoatletyce (Sewilla 1999)</code> | <code>kto zaprojektował medale, które będą wręczane podczas tegorocznych mistrzostw Europy juniorów w lekkoatletyce?</code> |
* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
```json
{
"loss": "MultipleNegativesRankingLoss",
"matryoshka_dims": [
768,
512,
256,
128,
64
],
"matryoshka_weights": [
1,
1,
1,
1,
1
],
"n_dims_per_step": -1
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 4
- `per_device_eval_batch_size`: 4
- `gradient_accumulation_steps`: 4
- `learning_rate`: 2e-05
- `num_train_epochs`: 5
- `lr_scheduler_type`: cosine
- `warmup_ratio`: 0.1
- `bf16`: True
- `tf32`: True
- `load_best_model_at_end`: True
- `optim`: adamw_torch_fused
- `batch_sampler`: no_duplicates
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 4
- `per_device_eval_batch_size`: 4
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 4
- `eval_accumulation_steps`: None
- `learning_rate`: 2e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 5
- `max_steps`: -1
- `lr_scheduler_type`: cosine
- `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`: True
- `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}
- `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`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
<details><summary>Click to expand</summary>
| Epoch | Step | Training Loss | dim_128_cosine_map@100 | dim_256_cosine_map@100 | dim_512_cosine_map@100 | dim_64_cosine_map@100 | dim_768_cosine_map@100 |
|:----------:|:-------:|:-------------:|:----------------------:|:----------------------:|:----------------------:|:---------------------:|:----------------------:|
| 0.0043 | 1 | 3.4442 | - | - | - | - | - |
| 0.0086 | 2 | 1.3916 | - | - | - | - | - |
| 0.0128 | 3 | 3.1284 | - | - | - | - | - |
| 0.0171 | 4 | 2.2049 | - | - | - | - | - |
| 0.0214 | 5 | 1.1821 | - | - | - | - | - |
| 0.0257 | 6 | 2.6633 | - | - | - | - | - |
| 0.0299 | 7 | 1.8173 | - | - | - | - | - |
| 0.0342 | 8 | 3.8366 | - | - | - | - | - |
| 0.0385 | 9 | 2.4439 | - | - | - | - | - |
| 0.0428 | 10 | 1.9733 | - | - | - | - | - |
| 0.0471 | 11 | 3.7611 | - | - | - | - | - |
| 0.0513 | 12 | 2.578 | - | - | - | - | - |
| 0.0556 | 13 | 1.656 | - | - | - | - | - |
| 0.0599 | 14 | 2.1508 | - | - | - | - | - |
| 0.0642 | 15 | 1.4962 | - | - | - | - | - |
| 0.0684 | 16 | 1.5743 | - | - | - | - | - |
| 0.0727 | 17 | 2.5404 | - | - | - | - | - |
| 0.0770 | 18 | 1.1436 | - | - | - | - | - |
| 0.0813 | 19 | 3.1786 | - | - | - | - | - |
| 0.0856 | 20 | 2.3377 | - | - | - | - | - |
| 0.0898 | 21 | 1.9693 | - | - | - | - | - |
| 0.0941 | 22 | 2.3942 | - | - | - | - | - |
| 0.0984 | 23 | 2.2259 | - | - | - | - | - |
| 0.1027 | 24 | 3.3127 | - | - | - | - | - |
| 0.1070 | 25 | 1.3368 | - | - | - | - | - |
| 0.1112 | 26 | 2.5546 | - | - | - | - | - |
| 0.1155 | 27 | 1.5828 | - | - | - | - | - |
| 0.1198 | 28 | 1.908 | - | - | - | - | - |
| 0.1241 | 29 | 1.9959 | - | - | - | - | - |
| 0.1283 | 30 | 1.2909 | - | - | - | - | - |
| 0.1326 | 31 | 1.7274 | - | - | - | - | - |
| 0.1369 | 32 | 1.9055 | - | - | - | - | - |
| 0.1412 | 33 | 3.3274 | - | - | - | - | - |
| 0.1455 | 34 | 2.5554 | - | - | - | - | - |
| 0.1497 | 35 | 1.7876 | - | - | - | - | - |
| 0.1540 | 36 | 2.0285 | - | - | - | - | - |
| 0.1583 | 37 | 3.0761 | - | - | - | - | - |
| 0.1626 | 38 | 3.4766 | - | - | - | - | - |
| 0.1668 | 39 | 1.4406 | - | - | - | - | - |
| 0.1711 | 40 | 1.7384 | - | - | - | - | - |
| 0.1754 | 41 | 1.8092 | - | - | - | - | - |
| 0.1797 | 42 | 3.146 | - | - | - | - | - |
| 0.1840 | 43 | 1.9202 | - | - | - | - | - |
| 0.1882 | 44 | 2.4776 | - | - | - | - | - |
| 0.1925 | 45 | 2.273 | - | - | - | - | - |
| 0.1968 | 46 | 1.2158 | - | - | - | - | - |
| 0.2011 | 47 | 0.6314 | - | - | - | - | - |
| 0.2053 | 48 | 1.2217 | - | - | - | - | - |
| 0.2096 | 49 | 1.7213 | - | - | - | - | - |
| 0.2139 | 50 | 2.1634 | - | - | - | - | - |
| 0.2182 | 51 | 1.0438 | - | - | - | - | - |
| 0.2225 | 52 | 1.4275 | - | - | - | - | - |
| 0.2267 | 53 | 1.6839 | - | - | - | - | - |
| 0.2310 | 54 | 1.5435 | - | - | - | - | - |
| 0.2353 | 55 | 2.3815 | - | - | - | - | - |
| 0.2396 | 56 | 2.3042 | - | - | - | - | - |
| 0.2439 | 57 | 2.3085 | - | - | - | - | - |
| 0.2481 | 58 | 2.0621 | - | - | - | - | - |
| 0.2524 | 59 | 1.339 | - | - | - | - | - |
| 0.2567 | 60 | 0.9167 | - | - | - | - | - |
| 0.2610 | 61 | 0.8112 | - | - | - | - | - |
| 0.2652 | 62 | 2.2327 | - | - | - | - | - |
| 0.2695 | 63 | 2.6571 | - | - | - | - | - |
| 0.2738 | 64 | 1.8199 | - | - | - | - | - |
| 0.2781 | 65 | 2.6123 | - | - | - | - | - |
| 0.2824 | 66 | 0.6182 | - | - | - | - | - |
| 0.2866 | 67 | 1.8278 | - | - | - | - | - |
| 0.2909 | 68 | 1.6969 | - | - | - | - | - |
| 0.2952 | 69 | 0.7902 | - | - | - | - | - |
| 0.2995 | 70 | 2.1857 | - | - | - | - | - |
| 0.3037 | 71 | 0.8371 | - | - | - | - | - |
| 0.3080 | 72 | 2.2118 | - | - | - | - | - |
| 0.3123 | 73 | 0.2464 | - | - | - | - | - |
| 0.3166 | 74 | 1.5362 | - | - | - | - | - |
| 0.3209 | 75 | 2.1047 | - | - | - | - | - |
| 0.3251 | 76 | 1.2654 | - | - | - | - | - |
| 0.3294 | 77 | 1.5016 | - | - | - | - | - |
| 0.3337 | 78 | 0.9273 | - | - | - | - | - |
| 0.3380 | 79 | 0.9228 | - | - | - | - | - |
| 0.3422 | 80 | 0.8002 | - | - | - | - | - |
| 0.3465 | 81 | 0.8325 | - | - | - | - | - |
| 0.3508 | 82 | 1.4914 | - | - | - | - | - |
| 0.3551 | 83 | 1.5896 | - | - | - | - | - |
| 0.3594 | 84 | 1.8716 | - | - | - | - | - |
| 0.3636 | 85 | 1.0927 | - | - | - | - | - |
| 0.3679 | 86 | 1.1389 | - | - | - | - | - |
| 0.3722 | 87 | 0.9251 | - | - | - | - | - |
| 0.3765 | 88 | 1.3966 | - | - | - | - | - |
| 0.3807 | 89 | 2.2866 | - | - | - | - | - |
| 0.3850 | 90 | 1.3756 | - | - | - | - | - |
| 0.3893 | 91 | 0.7271 | - | - | - | - | - |
| 0.3936 | 92 | 1.7267 | - | - | - | - | - |
| 0.3979 | 93 | 2.0597 | - | - | - | - | - |
| 0.4021 | 94 | 1.9522 | - | - | - | - | - |
| 0.4064 | 95 | 1.0192 | - | - | - | - | - |
| 0.4107 | 96 | 2.987 | - | - | - | - | - |
| 0.4150 | 97 | 1.9623 | - | - | - | - | - |
| 0.4193 | 98 | 2.0779 | - | - | - | - | - |
| 0.4235 | 99 | 1.6256 | - | - | - | - | - |
| 0.4278 | 100 | 1.6273 | - | - | - | - | - |
| 0.4321 | 101 | 2.848 | - | - | - | - | - |
| 0.4364 | 102 | 1.4129 | - | - | - | - | - |
| 0.4406 | 103 | 0.7578 | - | - | - | - | - |
| 0.4449 | 104 | 0.7026 | - | - | - | - | - |
| 0.4492 | 105 | 1.5958 | - | - | - | - | - |
| 0.4535 | 106 | 2.5135 | - | - | - | - | - |
| 0.4578 | 107 | 0.5845 | - | - | - | - | - |
| 0.4620 | 108 | 1.4398 | - | - | - | - | - |
| 0.4663 | 109 | 1.0315 | - | - | - | - | - |
| 0.4706 | 110 | 0.7233 | - | - | - | - | - |
| 0.4749 | 111 | 0.4793 | - | - | - | - | - |
| 0.4791 | 112 | 0.52 | - | - | - | - | - |
| 0.4834 | 113 | 0.4099 | - | - | - | - | - |
| 0.4877 | 114 | 1.2661 | - | - | - | - | - |
| 0.4920 | 115 | 1.7636 | - | - | - | - | - |
| 0.4963 | 116 | 2.0581 | - | - | - | - | - |
| 0.5005 | 117 | 0.9092 | - | - | - | - | - |
| 0.5048 | 118 | 1.5175 | - | - | - | - | - |
| 0.5091 | 119 | 1.7537 | - | - | - | - | - |
| 0.5134 | 120 | 0.984 | - | - | - | - | - |
| 0.5176 | 121 | 0.5867 | - | - | - | - | - |
| 0.5219 | 122 | 0.7082 | - | - | - | - | - |
| 0.5262 | 123 | 1.1787 | - | - | - | - | - |
| 0.5305 | 124 | 1.0118 | - | - | - | - | - |
| 0.5348 | 125 | 2.0169 | - | - | - | - | - |
| 0.5390 | 126 | 1.2881 | - | - | - | - | - |
| 0.5433 | 127 | 1.4748 | - | - | - | - | - |
| 0.5476 | 128 | 1.9601 | - | - | - | - | - |
| 0.5519 | 129 | 2.7434 | - | - | - | - | - |
| 0.5561 | 130 | 1.3171 | - | - | - | - | - |
| 0.5604 | 131 | 1.221 | - | - | - | - | - |
| 0.5647 | 132 | 1.24 | - | - | - | - | - |
| 0.5690 | 133 | 1.7489 | - | - | - | - | - |
| 0.5733 | 134 | 1.5888 | - | - | - | - | - |
| 0.5775 | 135 | 1.6449 | - | - | - | - | - |
| 0.5818 | 136 | 2.2163 | - | - | - | - | - |
| 0.5861 | 137 | 1.3148 | - | - | - | - | - |
| 0.5904 | 138 | 0.9209 | - | - | - | - | - |
| 0.5947 | 139 | 1.3826 | - | - | - | - | - |
| 0.5989 | 140 | 0.7924 | - | - | - | - | - |
| 0.6032 | 141 | 0.603 | - | - | - | - | - |
| 0.6075 | 142 | 1.6646 | - | - | - | - | - |
| 0.6118 | 143 | 1.2747 | - | - | - | - | - |
| 0.6160 | 144 | 2.4583 | - | - | - | - | - |
| 0.6203 | 145 | 2.0143 | - | - | - | - | - |
| 0.6246 | 146 | 1.8152 | - | - | - | - | - |
| 0.6289 | 147 | 0.6461 | - | - | - | - | - |
| 0.6332 | 148 | 0.5025 | - | - | - | - | - |
| 0.6374 | 149 | 0.6427 | - | - | - | - | - |
| 0.6417 | 150 | 1.6096 | - | - | - | - | - |
| 0.6460 | 151 | 3.0679 | - | - | - | - | - |
| 0.6503 | 152 | 2.8778 | - | - | - | - | - |
| 0.6545 | 153 | 1.2788 | - | - | - | - | - |
| 0.6588 | 154 | 0.5234 | - | - | - | - | - |
| 0.6631 | 155 | 1.2211 | - | - | - | - | - |
| 0.6674 | 156 | 1.5935 | - | - | - | - | - |
| 0.6717 | 157 | 1.892 | - | - | - | - | - |
| 0.6759 | 158 | 0.9767 | - | - | - | - | - |
| 0.6802 | 159 | 1.8692 | - | - | - | - | - |
| 0.6845 | 160 | 1.9853 | - | - | - | - | - |
| 0.6888 | 161 | 0.9568 | - | - | - | - | - |
| 0.6930 | 162 | 0.526 | - | - | - | - | - |
| 0.6973 | 163 | 0.6527 | - | - | - | - | - |
| 0.7016 | 164 | 1.2888 | - | - | - | - | - |
| 0.7059 | 165 | 0.9485 | - | - | - | - | - |
| 0.7102 | 166 | 2.3512 | - | - | - | - | - |
| 0.7144 | 167 | 2.5909 | - | - | - | - | - |
| 0.7187 | 168 | 1.9271 | - | - | - | - | - |
| 0.7230 | 169 | 1.7218 | - | - | - | - | - |
| 0.7273 | 170 | 1.6517 | - | - | - | - | - |
| 0.7316 | 171 | 1.3378 | - | - | - | - | - |
| 0.7358 | 172 | 1.5502 | - | - | - | - | - |
| 0.7401 | 173 | 1.7182 | - | - | - | - | - |
| 0.7444 | 174 | 2.0422 | - | - | - | - | - |
| 0.7487 | 175 | 2.1827 | - | - | - | - | - |
| 0.7529 | 176 | 0.917 | - | - | - | - | - |
| 0.7572 | 177 | 2.4209 | - | - | - | - | - |
| 0.7615 | 178 | 0.7705 | - | - | - | - | - |
| 0.7658 | 179 | 0.4089 | - | - | - | - | - |
| 0.7701 | 180 | 0.7368 | - | - | - | - | - |
| 0.7743 | 181 | 0.7583 | - | - | - | - | - |
| 0.7786 | 182 | 1.2686 | - | - | - | - | - |
| 0.7829 | 183 | 0.9401 | - | - | - | - | - |
| 0.7872 | 184 | 1.9668 | - | - | - | - | - |
| 0.7914 | 185 | 1.7905 | - | - | - | - | - |
| 0.7957 | 186 | 0.4372 | - | - | - | - | - |
| 0.8 | 187 | 1.3618 | - | - | - | - | - |
| 0.8043 | 188 | 1.0816 | - | - | - | - | - |
| 0.8086 | 189 | 0.5696 | - | - | - | - | - |
| 0.8128 | 190 | 0.7607 | - | - | - | - | - |
| 0.8171 | 191 | 2.8499 | - | - | - | - | - |
| 0.8214 | 192 | 2.251 | - | - | - | - | - |
| 0.8257 | 193 | 2.3819 | - | - | - | - | - |
| 0.8299 | 194 | 0.4848 | - | - | - | - | - |
| 0.8342 | 195 | 1.0241 | - | - | - | - | - |
| 0.8385 | 196 | 0.4664 | - | - | - | - | - |
| 0.8428 | 197 | 1.0253 | - | - | - | - | - |
| 0.8471 | 198 | 1.3517 | - | - | - | - | - |
| 0.8513 | 199 | 1.5231 | - | - | - | - | - |
| 0.8556 | 200 | 1.9424 | - | - | - | - | - |
| 0.8599 | 201 | 1.6661 | - | - | - | - | - |
| 0.8642 | 202 | 0.204 | - | - | - | - | - |
| 0.8684 | 203 | 1.805 | - | - | - | - | - |
| 0.8727 | 204 | 1.2863 | - | - | - | - | - |
| 0.8770 | 205 | 2.3292 | - | - | - | - | - |
| 0.8813 | 206 | 1.4561 | - | - | - | - | - |
| 0.8856 | 207 | 0.4618 | - | - | - | - | - |
| 0.8898 | 208 | 0.9744 | - | - | - | - | - |
| 0.8941 | 209 | 0.5276 | - | - | - | - | - |
| 0.8984 | 210 | 0.8812 | - | - | - | - | - |
| 0.9027 | 211 | 0.6778 | - | - | - | - | - |
| 0.9070 | 212 | 1.2382 | - | - | - | - | - |
| 0.9112 | 213 | 0.7281 | - | - | - | - | - |
| 0.9155 | 214 | 1.4499 | - | - | - | - | - |
| 0.9198 | 215 | 1.8433 | - | - | - | - | - |
| 0.9241 | 216 | 0.4683 | - | - | - | - | - |
| 0.9283 | 217 | 0.7045 | - | - | - | - | - |
| 0.9326 | 218 | 1.0181 | - | - | - | - | - |
| 0.9369 | 219 | 1.104 | - | - | - | - | - |
| 0.9412 | 220 | 0.4282 | - | - | - | - | - |
| 0.9455 | 221 | 1.8888 | - | - | - | - | - |
| 0.9497 | 222 | 0.7936 | - | - | - | - | - |
| 0.9540 | 223 | 2.5346 | - | - | - | - | - |
| 0.9583 | 224 | 0.8337 | - | - | - | - | - |
| 0.9626 | 225 | 1.6245 | - | - | - | - | - |
| 0.9668 | 226 | 0.8955 | - | - | - | - | - |
| 0.9711 | 227 | 0.9813 | - | - | - | - | - |
| 0.9754 | 228 | 0.9429 | - | - | - | - | - |
| 0.9797 | 229 | 1.5297 | - | - | - | - | - |
| 0.9840 | 230 | 1.0861 | - | - | - | - | - |
| 0.9882 | 231 | 1.5228 | - | - | - | - | - |
| 0.9925 | 232 | 0.8545 | - | - | - | - | - |
| 0.9968 | 233 | 2.3052 | 0.3541 | 0.3928 | 0.3969 | 0.2990 | 0.4032 |
| 1.0011 | 234 | 0.5205 | - | - | - | - | - |
| 1.0053 | 235 | 1.6719 | - | - | - | - | - |
| 1.0096 | 236 | 0.5632 | - | - | - | - | - |
| 1.0139 | 237 | 0.3602 | - | - | - | - | - |
| 1.0182 | 238 | 0.4581 | - | - | - | - | - |
| 1.0225 | 239 | 1.7666 | - | - | - | - | - |
| 1.0267 | 240 | 0.925 | - | - | - | - | - |
| 1.0310 | 241 | 0.9264 | - | - | - | - | - |
| 1.0353 | 242 | 1.5405 | - | - | - | - | - |
| 1.0396 | 243 | 0.5346 | - | - | - | - | - |
| 1.0439 | 244 | 1.1432 | - | - | - | - | - |
| 1.0481 | 245 | 2.7575 | - | - | - | - | - |
| 1.0524 | 246 | 0.6409 | - | - | - | - | - |
| 1.0567 | 247 | 0.5409 | - | - | - | - | - |
| 1.0610 | 248 | 0.5996 | - | - | - | - | - |
| 1.0652 | 249 | 0.6733 | - | - | - | - | - |
| 1.0695 | 250 | 0.9336 | - | - | - | - | - |
| 1.0738 | 251 | 1.4003 | - | - | - | - | - |
| 1.0781 | 252 | 0.544 | - | - | - | - | - |
| 1.0824 | 253 | 1.871 | - | - | - | - | - |
| 1.0866 | 254 | 1.8823 | - | - | - | - | - |
| 1.0909 | 255 | 0.9452 | - | - | - | - | - |
| 1.0952 | 256 | 0.5241 | - | - | - | - | - |
| 1.0995 | 257 | 0.5349 | - | - | - | - | - |
| 1.1037 | 258 | 1.7114 | - | - | - | - | - |
| 1.1080 | 259 | 0.6899 | - | - | - | - | - |
| 1.1123 | 260 | 0.657 | - | - | - | - | - |
| 1.1166 | 261 | 0.5195 | - | - | - | - | - |
| 1.1209 | 262 | 1.3961 | - | - | - | - | - |
| 1.1251 | 263 | 0.429 | - | - | - | - | - |
| 1.1294 | 264 | 0.0763 | - | - | - | - | - |
| 1.1337 | 265 | 0.7172 | - | - | - | - | - |
| 1.1380 | 266 | 0.408 | - | - | - | - | - |
| 1.1422 | 267 | 0.7704 | - | - | - | - | - |
| 1.1465 | 268 | 0.7025 | - | - | - | - | - |
| 1.1508 | 269 | 0.4682 | - | - | - | - | - |
| 1.1551 | 270 | 0.4666 | - | - | - | - | - |
| 1.1594 | 271 | 1.8544 | - | - | - | - | - |
| 1.1636 | 272 | 0.5303 | - | - | - | - | - |
| 1.1679 | 273 | 0.6873 | - | - | - | - | - |
| 1.1722 | 274 | 0.6294 | - | - | - | - | - |
| 1.1765 | 275 | 1.7406 | - | - | - | - | - |
| 1.1807 | 276 | 0.9965 | - | - | - | - | - |
| 1.1850 | 277 | 0.5852 | - | - | - | - | - |
| 1.1893 | 278 | 0.7836 | - | - | - | - | - |
| 1.1936 | 279 | 0.5689 | - | - | - | - | - |
| 1.1979 | 280 | 0.3104 | - | - | - | - | - |
| 1.2021 | 281 | 0.1838 | - | - | - | - | - |
| 1.2064 | 282 | 1.2004 | - | - | - | - | - |
| 1.2107 | 283 | 0.2965 | - | - | - | - | - |
| 1.2150 | 284 | 0.8235 | - | - | - | - | - |
| 1.2193 | 285 | 0.4341 | - | - | - | - | - |
| 1.2235 | 286 | 0.8613 | - | - | - | - | - |
| 1.2278 | 287 | 0.2466 | - | - | - | - | - |
| 1.2321 | 288 | 0.4417 | - | - | - | - | - |
| 1.2364 | 289 | 0.3849 | - | - | - | - | - |
| 1.2406 | 290 | 1.0044 | - | - | - | - | - |
| 1.2449 | 291 | 0.4567 | - | - | - | - | - |
| 1.2492 | 292 | 0.7786 | - | - | - | - | - |
| 1.2535 | 293 | 0.1726 | - | - | - | - | - |
| 1.2578 | 294 | 0.6764 | - | - | - | - | - |
| 1.2620 | 295 | 0.5581 | - | - | - | - | - |
| 1.2663 | 296 | 0.3714 | - | - | - | - | - |
| 1.2706 | 297 | 0.4684 | - | - | - | - | - |
| 1.2749 | 298 | 1.197 | - | - | - | - | - |
| 1.2791 | 299 | 0.3273 | - | - | - | - | - |
| 1.2834 | 300 | 0.1804 | - | - | - | - | - |
| 1.2877 | 301 | 0.5446 | - | - | - | - | - |
| 1.2920 | 302 | 0.978 | - | - | - | - | - |
| 1.2963 | 303 | 0.1825 | - | - | - | - | - |
| 1.3005 | 304 | 0.8737 | - | - | - | - | - |
| 1.3048 | 305 | 0.1771 | - | - | - | - | - |
| 1.3091 | 306 | 0.1146 | - | - | - | - | - |
| 1.3134 | 307 | 0.2057 | - | - | - | - | - |
| 1.3176 | 308 | 0.7019 | - | - | - | - | - |
| 1.3219 | 309 | 0.4566 | - | - | - | - | - |
| 1.3262 | 310 | 0.5807 | - | - | - | - | - |
| 1.3305 | 311 | 0.299 | - | - | - | - | - |
| 1.3348 | 312 | 0.5087 | - | - | - | - | - |
| 1.3390 | 313 | 0.4208 | - | - | - | - | - |
| 1.3433 | 314 | 0.1847 | - | - | - | - | - |
| 1.3476 | 315 | 0.5001 | - | - | - | - | - |
| 1.3519 | 316 | 0.1688 | - | - | - | - | - |
| 1.3561 | 317 | 0.2255 | - | - | - | - | - |
| 1.3604 | 318 | 0.4908 | - | - | - | - | - |
| 1.3647 | 319 | 0.1893 | - | - | - | - | - |
| 1.3690 | 320 | 0.2928 | - | - | - | - | - |
| 1.3733 | 321 | 0.1817 | - | - | - | - | - |
| 1.3775 | 322 | 0.6634 | - | - | - | - | - |
| 1.3818 | 323 | 0.9223 | - | - | - | - | - |
| 1.3861 | 324 | 0.2463 | - | - | - | - | - |
| 1.3904 | 325 | 0.3846 | - | - | - | - | - |
| 1.3947 | 326 | 0.789 | - | - | - | - | - |
| 1.3989 | 327 | 0.6919 | - | - | - | - | - |
| 1.4032 | 328 | 0.3168 | - | - | - | - | - |
| 1.4075 | 329 | 0.4332 | - | - | - | - | - |
| 1.4118 | 330 | 0.9224 | - | - | - | - | - |
| 1.4160 | 331 | 0.2678 | - | - | - | - | - |
| 1.4203 | 332 | 0.2826 | - | - | - | - | - |
| 1.4246 | 333 | 0.1273 | - | - | - | - | - |
| 1.4289 | 334 | 0.3071 | - | - | - | - | - |
| 1.4332 | 335 | 0.3195 | - | - | - | - | - |
| 1.4374 | 336 | 0.3031 | - | - | - | - | - |
| 1.4417 | 337 | 0.2312 | - | - | - | - | - |
| 1.4460 | 338 | 0.0635 | - | - | - | - | - |
| 1.4503 | 339 | 1.1888 | - | - | - | - | - |
| 1.4545 | 340 | 0.3506 | - | - | - | - | - |
| 1.4588 | 341 | 0.0363 | - | - | - | - | - |
| 1.4631 | 342 | 0.2748 | - | - | - | - | - |
| 1.4674 | 343 | 0.1862 | - | - | - | - | - |
| 1.4717 | 344 | 0.1419 | - | - | - | - | - |
| 1.4759 | 345 | 0.2381 | - | - | - | - | - |
| 1.4802 | 346 | 0.0541 | - | - | - | - | - |
| 1.4845 | 347 | 0.1185 | - | - | - | - | - |
| 1.4888 | 348 | 0.4528 | - | - | - | - | - |
| 1.4930 | 349 | 0.4922 | - | - | - | - | - |
| 1.4973 | 350 | 0.1744 | - | - | - | - | - |
| 1.5016 | 351 | 0.241 | - | - | - | - | - |
| 1.5059 | 352 | 0.1481 | - | - | - | - | - |
| 1.5102 | 353 | 0.3377 | - | - | - | - | - |
| 1.5144 | 354 | 0.2208 | - | - | - | - | - |
| 1.5187 | 355 | 0.054 | - | - | - | - | - |
| 1.5230 | 356 | 0.1506 | - | - | - | - | - |
| 1.5273 | 357 | 0.0794 | - | - | - | - | - |
| 1.5316 | 358 | 0.1631 | - | - | - | - | - |
| 1.5358 | 359 | 0.1571 | - | - | - | - | - |
| 1.5401 | 360 | 0.2831 | - | - | - | - | - |
| 1.5444 | 361 | 0.3486 | - | - | - | - | - |
| 1.5487 | 362 | 0.6273 | - | - | - | - | - |
| 1.5529 | 363 | 1.0274 | - | - | - | - | - |
| 1.5572 | 364 | 0.269 | - | - | - | - | - |
| 1.5615 | 365 | 0.1897 | - | - | - | - | - |
| 1.5658 | 366 | 0.1987 | - | - | - | - | - |
| 1.5701 | 367 | 0.1943 | - | - | - | - | - |
| 1.5743 | 368 | 0.4424 | - | - | - | - | - |
| 1.5786 | 369 | 0.0848 | - | - | - | - | - |
| 1.5829 | 370 | 0.3504 | - | - | - | - | - |
| 1.5872 | 371 | 0.1759 | - | - | - | - | - |
| 1.5914 | 372 | 0.1168 | - | - | - | - | - |
| 1.5957 | 373 | 0.0824 | - | - | - | - | - |
| 1.6 | 374 | 0.2637 | - | - | - | - | - |
| 1.6043 | 375 | 0.2454 | - | - | - | - | - |
| 1.6086 | 376 | 0.1974 | - | - | - | - | - |
| 1.6128 | 377 | 0.5961 | - | - | - | - | - |
| 1.6171 | 378 | 1.0758 | - | - | - | - | - |
| 1.6214 | 379 | 0.6134 | - | - | - | - | - |
| 1.6257 | 380 | 0.3244 | - | - | - | - | - |
| 1.6299 | 381 | 0.0201 | - | - | - | - | - |
| 1.6342 | 382 | 0.1052 | - | - | - | - | - |
| 1.6385 | 383 | 0.2025 | - | - | - | - | - |
| 1.6428 | 384 | 0.9475 | - | - | - | - | - |
| 1.6471 | 385 | 1.3788 | - | - | - | - | - |
| 1.6513 | 386 | 0.4879 | - | - | - | - | - |
| 1.6556 | 387 | 0.226 | - | - | - | - | - |
| 1.6599 | 388 | 0.0576 | - | - | - | - | - |
| 1.6642 | 389 | 0.4956 | - | - | - | - | - |
| 1.6684 | 390 | 0.3145 | - | - | - | - | - |
| 1.6727 | 391 | 0.5387 | - | - | - | - | - |
| 1.6770 | 392 | 0.5391 | - | - | - | - | - |
| 1.6813 | 393 | 0.6977 | - | - | - | - | - |
| 1.6856 | 394 | 0.4331 | - | - | - | - | - |
| 1.6898 | 395 | 0.6582 | - | - | - | - | - |
| 1.6941 | 396 | 0.5774 | - | - | - | - | - |
| 1.6984 | 397 | 0.1363 | - | - | - | - | - |
| 1.7027 | 398 | 0.1877 | - | - | - | - | - |
| 1.7070 | 399 | 0.3772 | - | - | - | - | - |
| 1.7112 | 400 | 0.6645 | - | - | - | - | - |
| 1.7155 | 401 | 0.8067 | - | - | - | - | - |
| 1.7198 | 402 | 0.1889 | - | - | - | - | - |
| 1.7241 | 403 | 0.3212 | - | - | - | - | - |
| 1.7283 | 404 | 0.6867 | - | - | - | - | - |
| 1.7326 | 405 | 0.228 | - | - | - | - | - |
| 1.7369 | 406 | 0.4952 | - | - | - | - | - |
| 1.7412 | 407 | 0.5718 | - | - | - | - | - |
| 1.7455 | 408 | 0.2607 | - | - | - | - | - |
| 1.7497 | 409 | 0.3326 | - | - | - | - | - |
| 1.7540 | 410 | 0.5813 | - | - | - | - | - |
| 1.7583 | 411 | 0.8952 | - | - | - | - | - |
| 1.7626 | 412 | 0.0735 | - | - | - | - | - |
| 1.7668 | 413 | 0.1031 | - | - | - | - | - |
| 1.7711 | 414 | 0.0321 | - | - | - | - | - |
| 1.7754 | 415 | 0.0909 | - | - | - | - | - |
| 1.7797 | 416 | 0.4591 | - | - | - | - | - |
| 1.7840 | 417 | 0.2188 | - | - | - | - | - |
| 1.7882 | 418 | 0.1857 | - | - | - | - | - |
| 1.7925 | 419 | 0.4137 | - | - | - | - | - |
| 1.7968 | 420 | 0.0631 | - | - | - | - | - |
| 1.8011 | 421 | 0.3535 | - | - | - | - | - |
| 1.8053 | 422 | 0.467 | - | - | - | - | - |
| 1.8096 | 423 | 0.0427 | - | - | - | - | - |
| 1.8139 | 424 | 0.7846 | - | - | - | - | - |
| 1.8182 | 425 | 0.8365 | - | - | - | - | - |
| 1.8225 | 426 | 0.1746 | - | - | - | - | - |
| 1.8267 | 427 | 0.3084 | - | - | - | - | - |
| 1.8310 | 428 | 0.0457 | - | - | - | - | - |
| 1.8353 | 429 | 0.108 | - | - | - | - | - |
| 1.8396 | 430 | 0.5707 | - | - | - | - | - |
| 1.8439 | 431 | 0.2809 | - | - | - | - | - |
| 1.8481 | 432 | 0.162 | - | - | - | - | - |
| 1.8524 | 433 | 0.3929 | - | - | - | - | - |
| 1.8567 | 434 | 0.2679 | - | - | - | - | - |
| 1.8610 | 435 | 0.4651 | - | - | - | - | - |
| 1.8652 | 436 | 0.3847 | - | - | - | - | - |
| 1.8695 | 437 | 0.3955 | - | - | - | - | - |
| 1.8738 | 438 | 0.2116 | - | - | - | - | - |
| 1.8781 | 439 | 0.7634 | - | - | - | - | - |
| 1.8824 | 440 | 0.1442 | - | - | - | - | - |
| 1.8866 | 441 | 0.0805 | - | - | - | - | - |
| 1.8909 | 442 | 0.0605 | - | - | - | - | - |
| 1.8952 | 443 | 0.1937 | - | - | - | - | - |
| 1.8995 | 444 | 0.1044 | - | - | - | - | - |
| 1.9037 | 445 | 0.5122 | - | - | - | - | - |
| 1.9080 | 446 | 0.1195 | - | - | - | - | - |
| 1.9123 | 447 | 0.1904 | - | - | - | - | - |
| 1.9166 | 448 | 0.2764 | - | - | - | - | - |
| 1.9209 | 449 | 0.5287 | - | - | - | - | - |
| 1.9251 | 450 | 0.1051 | - | - | - | - | - |
| 1.9294 | 451 | 0.1825 | - | - | - | - | - |
| 1.9337 | 452 | 0.0838 | - | - | - | - | - |
| 1.9380 | 453 | 0.0739 | - | - | - | - | - |
| 1.9422 | 454 | 0.0988 | - | - | - | - | - |
| 1.9465 | 455 | 0.2542 | - | - | - | - | - |
| 1.9508 | 456 | 0.1043 | - | - | - | - | - |
| 1.9551 | 457 | 0.4259 | - | - | - | - | - |
| 1.9594 | 458 | 0.1923 | - | - | - | - | - |
| 1.9636 | 459 | 0.2651 | - | - | - | - | - |
| 1.9679 | 460 | 0.0533 | - | - | - | - | - |
| 1.9722 | 461 | 0.2306 | - | - | - | - | - |
| 1.9765 | 462 | 0.168 | - | - | - | - | - |
| 1.9807 | 463 | 0.3181 | - | - | - | - | - |
| 1.9850 | 464 | 0.042 | - | - | - | - | - |
| 1.9893 | 465 | 0.0833 | - | - | - | - | - |
| 1.9936 | 466 | 0.2425 | - | - | - | - | - |
| **1.9979** | **467** | **0.7451** | **0.3624** | **0.3819** | **0.3987** | **0.3061** | **0.3968** |
| 2.0021 | 468 | 0.1784 | - | - | - | - | - |
| 2.0064 | 469 | 0.2073 | - | - | - | - | - |
| 2.0107 | 470 | 0.211 | - | - | - | - | - |
| 2.0150 | 471 | 0.0456 | - | - | - | - | - |
| 2.0193 | 472 | 0.1354 | - | - | - | - | - |
| 2.0235 | 473 | 0.1245 | - | - | - | - | - |
| 2.0278 | 474 | 0.0861 | - | - | - | - | - |
| 2.0321 | 475 | 0.0397 | - | - | - | - | - |
| 2.0364 | 476 | 0.0925 | - | - | - | - | - |
| 2.0406 | 477 | 0.0652 | - | - | - | - | - |
| 2.0449 | 478 | 0.4905 | - | - | - | - | - |
| 2.0492 | 479 | 0.1338 | - | - | - | - | - |
| 2.0535 | 480 | 0.0463 | - | - | - | - | - |
| 2.0578 | 481 | 0.1399 | - | - | - | - | - |
| 2.0620 | 482 | 0.0192 | - | - | - | - | - |
| 2.0663 | 483 | 0.1343 | - | - | - | - | - |
| 2.0706 | 484 | 0.1027 | - | - | - | - | - |
| 2.0749 | 485 | 0.1746 | - | - | - | - | - |
| 2.0791 | 486 | 0.584 | - | - | - | - | - |
| 2.0834 | 487 | 0.2704 | - | - | - | - | - |
| 2.0877 | 488 | 0.3391 | - | - | - | - | - |
| 2.0920 | 489 | 0.0892 | - | - | - | - | - |
| 2.0963 | 490 | 0.1273 | - | - | - | - | - |
| 2.1005 | 491 | 0.0644 | - | - | - | - | - |
| 2.1048 | 492 | 0.2457 | - | - | - | - | - |
| 2.1091 | 493 | 0.147 | - | - | - | - | - |
| 2.1134 | 494 | 0.2746 | - | - | - | - | - |
| 2.1176 | 495 | 0.1425 | - | - | - | - | - |
| 2.1219 | 496 | 0.198 | - | - | - | - | - |
| 2.1262 | 497 | 0.1079 | - | - | - | - | - |
| 2.1305 | 498 | 0.0583 | - | - | - | - | - |
| 2.1348 | 499 | 0.0646 | - | - | - | - | - |
| 2.1390 | 500 | 0.1751 | - | - | - | - | - |
| 2.1433 | 501 | 0.2996 | - | - | - | - | - |
| 2.1476 | 502 | 0.1059 | - | - | - | - | - |
| 2.1519 | 503 | 0.162 | - | - | - | - | - |
| 2.1561 | 504 | 0.1426 | - | - | - | - | - |
| 2.1604 | 505 | 0.4076 | - | - | - | - | - |
| 2.1647 | 506 | 0.0968 | - | - | - | - | - |
| 2.1690 | 507 | 0.0867 | - | - | - | - | - |
| 2.1733 | 508 | 0.0713 | - | - | - | - | - |
| 2.1775 | 509 | 0.2186 | - | - | - | - | - |
| 2.1818 | 510 | 0.099 | - | - | - | - | - |
| 2.1861 | 511 | 0.1216 | - | - | - | - | - |
| 2.1904 | 512 | 0.3812 | - | - | - | - | - |
| 2.1947 | 513 | 0.1481 | - | - | - | - | - |
| 2.1989 | 514 | 0.1637 | - | - | - | - | - |
| 2.2032 | 515 | 0.1068 | - | - | - | - | - |
| 2.2075 | 516 | 0.1002 | - | - | - | - | - |
| 2.2118 | 517 | 0.2612 | - | - | - | - | - |
| 2.2160 | 518 | 0.1599 | - | - | - | - | - |
| 2.2203 | 519 | 0.0513 | - | - | - | - | - |
| 2.2246 | 520 | 0.1409 | - | - | - | - | - |
| 2.2289 | 521 | 0.0171 | - | - | - | - | - |
| 2.2332 | 522 | 0.059 | - | - | - | - | - |
| 2.2374 | 523 | 0.2391 | - | - | - | - | - |
| 2.2417 | 524 | 0.2119 | - | - | - | - | - |
| 2.2460 | 525 | 0.1562 | - | - | - | - | - |
| 2.2503 | 526 | 0.3576 | - | - | - | - | - |
| 2.2545 | 527 | 0.3094 | - | - | - | - | - |
| 2.2588 | 528 | 0.0472 | - | - | - | - | - |
| 2.2631 | 529 | 0.1259 | - | - | - | - | - |
| 2.2674 | 530 | 0.0282 | - | - | - | - | - |
| 2.2717 | 531 | 0.5926 | - | - | - | - | - |
| 2.2759 | 532 | 0.1211 | - | - | - | - | - |
| 2.2802 | 533 | 0.0334 | - | - | - | - | - |
| 2.2845 | 534 | 0.0233 | - | - | - | - | - |
| 2.2888 | 535 | 0.0937 | - | - | - | - | - |
| 2.2930 | 536 | 0.0868 | - | - | - | - | - |
| 2.2973 | 537 | 0.0235 | - | - | - | - | - |
| 2.3016 | 538 | 0.1052 | - | - | - | - | - |
| 2.3059 | 539 | 0.0276 | - | - | - | - | - |
| 2.3102 | 540 | 0.0682 | - | - | - | - | - |
| 2.3144 | 541 | 0.0945 | - | - | - | - | - |
| 2.3187 | 542 | 0.0401 | - | - | - | - | - |
| 2.3230 | 543 | 0.0883 | - | - | - | - | - |
| 2.3273 | 544 | 0.0358 | - | - | - | - | - |
| 2.3316 | 545 | 0.0498 | - | - | - | - | - |
| 2.3358 | 546 | 0.0238 | - | - | - | - | - |
| 2.3401 | 547 | 0.2935 | - | - | - | - | - |
| 2.3444 | 548 | 0.0459 | - | - | - | - | - |
| 2.3487 | 549 | 0.0473 | - | - | - | - | - |
| 2.3529 | 550 | 0.1763 | - | - | - | - | - |
| 2.3572 | 551 | 0.125 | - | - | - | - | - |
| 2.3615 | 552 | 0.1579 | - | - | - | - | - |
| 2.3658 | 553 | 0.0526 | - | - | - | - | - |
| 2.3701 | 554 | 0.0522 | - | - | - | - | - |
| 2.3743 | 555 | 0.2429 | - | - | - | - | - |
| 2.3786 | 556 | 0.097 | - | - | - | - | - |
| 2.3829 | 557 | 0.1971 | - | - | - | - | - |
| 2.3872 | 558 | 0.0722 | - | - | - | - | - |
| 2.3914 | 559 | 0.3371 | - | - | - | - | - |
| 2.3957 | 560 | 0.4065 | - | - | - | - | - |
| 2.4 | 561 | 0.8116 | - | - | - | - | - |
| 2.4043 | 562 | 0.0576 | - | - | - | - | - |
| 2.4086 | 563 | 0.1228 | - | - | - | - | - |
| 2.4128 | 564 | 0.3299 | - | - | - | - | - |
| 2.4171 | 565 | 0.3528 | - | - | - | - | - |
| 2.4214 | 566 | 0.0664 | - | - | - | - | - |
| 2.4257 | 567 | 0.0782 | - | - | - | - | - |
| 2.4299 | 568 | 0.0353 | - | - | - | - | - |
| 2.4342 | 569 | 0.0786 | - | - | - | - | - |
| 2.4385 | 570 | 0.179 | - | - | - | - | - |
| 2.4428 | 571 | 0.0167 | - | - | - | - | - |
| 2.4471 | 572 | 0.0309 | - | - | - | - | - |
| 2.4513 | 573 | 0.2699 | - | - | - | - | - |
| 2.4556 | 574 | 0.0223 | - | - | - | - | - |
| 2.4599 | 575 | 0.0062 | - | - | - | - | - |
| 2.4642 | 576 | 0.0825 | - | - | - | - | - |
| 2.4684 | 577 | 0.1334 | - | - | - | - | - |
| 2.4727 | 578 | 0.0161 | - | - | - | - | - |
| 2.4770 | 579 | 0.0136 | - | - | - | - | - |
| 2.4813 | 580 | 0.0477 | - | - | - | - | - |
| 2.4856 | 581 | 0.0869 | - | - | - | - | - |
| 2.4898 | 582 | 0.0569 | - | - | - | - | - |
| 2.4941 | 583 | 0.1039 | - | - | - | - | - |
| 2.4984 | 584 | 0.0891 | - | - | - | - | - |
| 2.5027 | 585 | 0.0251 | - | - | - | - | - |
| 2.5070 | 586 | 0.0532 | - | - | - | - | - |
| 2.5112 | 587 | 0.0665 | - | - | - | - | - |
| 2.5155 | 588 | 0.0361 | - | - | - | - | - |
| 2.5198 | 589 | 0.0126 | - | - | - | - | - |
| 2.5241 | 590 | 0.0614 | - | - | - | - | - |
| 2.5283 | 591 | 0.0584 | - | - | - | - | - |
| 2.5326 | 592 | 0.0137 | - | - | - | - | - |
| 2.5369 | 593 | 0.1374 | - | - | - | - | - |
| 2.5412 | 594 | 0.0723 | - | - | - | - | - |
| 2.5455 | 595 | 0.0739 | - | - | - | - | - |
| 2.5497 | 596 | 0.388 | - | - | - | - | - |
| 2.5540 | 597 | 0.201 | - | - | - | - | - |
| 2.5583 | 598 | 0.0377 | - | - | - | - | - |
| 2.5626 | 599 | 0.0653 | - | - | - | - | - |
| 2.5668 | 600 | 0.0748 | - | - | - | - | - |
| 2.5711 | 601 | 0.0246 | - | - | - | - | - |
| 2.5754 | 602 | 0.0277 | - | - | - | - | - |
| 2.5797 | 603 | 0.0216 | - | - | - | - | - |
| 2.5840 | 604 | 0.0996 | - | - | - | - | - |
| 2.5882 | 605 | 0.1079 | - | - | - | - | - |
| 2.5925 | 606 | 0.0388 | - | - | - | - | - |
| 2.5968 | 607 | 0.0196 | - | - | - | - | - |
| 2.6011 | 608 | 0.051 | - | - | - | - | - |
| 2.6053 | 609 | 0.2019 | - | - | - | - | - |
| 2.6096 | 610 | 0.0523 | - | - | - | - | - |
| 2.6139 | 611 | 0.2106 | - | - | - | - | - |
| 2.6182 | 612 | 0.0803 | - | - | - | - | - |
| 2.6225 | 613 | 0.1198 | - | - | - | - | - |
| 2.6267 | 614 | 0.0261 | - | - | - | - | - |
| 2.6310 | 615 | 0.006 | - | - | - | - | - |
| 2.6353 | 616 | 0.0124 | - | - | - | - | - |
| 2.6396 | 617 | 0.0184 | - | - | - | - | - |
| 2.6439 | 618 | 0.0586 | - | - | - | - | - |
| 2.6481 | 619 | 0.2706 | - | - | - | - | - |
| 2.6524 | 620 | 0.1514 | - | - | - | - | - |
| 2.6567 | 621 | 0.0402 | - | - | - | - | - |
| 2.6610 | 622 | 0.0213 | - | - | - | - | - |
| 2.6652 | 623 | 0.0633 | - | - | - | - | - |
| 2.6695 | 624 | 0.1043 | - | - | - | - | - |
| 2.6738 | 625 | 0.0199 | - | - | - | - | - |
| 2.6781 | 626 | 0.1759 | - | - | - | - | - |
| 2.6824 | 627 | 0.1978 | - | - | - | - | - |
| 2.6866 | 628 | 0.1043 | - | - | - | - | - |
| 2.6909 | 629 | 0.1454 | - | - | - | - | - |
| 2.6952 | 630 | 0.0462 | - | - | - | - | - |
| 2.6995 | 631 | 0.0308 | - | - | - | - | - |
| 2.7037 | 632 | 0.0379 | - | - | - | - | - |
| 2.7080 | 633 | 0.3084 | - | - | - | - | - |
| 2.7123 | 634 | 0.1094 | - | - | - | - | - |
| 2.7166 | 635 | 0.1527 | - | - | - | - | - |
| 2.7209 | 636 | 0.1717 | - | - | - | - | - |
| 2.7251 | 637 | 0.4347 | - | - | - | - | - |
| 2.7294 | 638 | 0.128 | - | - | - | - | - |
| 2.7337 | 639 | 0.0658 | - | - | - | - | - |
| 2.7380 | 640 | 0.1678 | - | - | - | - | - |
| 2.7422 | 641 | 0.0508 | - | - | - | - | - |
| 2.7465 | 642 | 0.0797 | - | - | - | - | - |
| 2.7508 | 643 | 0.081 | - | - | - | - | - |
| 2.7551 | 644 | 0.1065 | - | - | - | - | - |
| 2.7594 | 645 | 0.1165 | - | - | - | - | - |
| 2.7636 | 646 | 0.0127 | - | - | - | - | - |
| 2.7679 | 647 | 0.0789 | - | - | - | - | - |
| 2.7722 | 648 | 0.0042 | - | - | - | - | - |
| 2.7765 | 649 | 0.014 | - | - | - | - | - |
| 2.7807 | 650 | 0.0638 | - | - | - | - | - |
| 2.7850 | 651 | 0.0376 | - | - | - | - | - |
| 2.7893 | 652 | 0.2348 | - | - | - | - | - |
| 2.7936 | 653 | 0.0505 | - | - | - | - | - |
| 2.7979 | 654 | 0.0194 | - | - | - | - | - |
| 2.8021 | 655 | 0.0507 | - | - | - | - | - |
| 2.8064 | 656 | 0.0825 | - | - | - | - | - |
| 2.8107 | 657 | 0.0156 | - | - | - | - | - |
| 2.8150 | 658 | 0.4371 | - | - | - | - | - |
| 2.8193 | 659 | 0.2948 | - | - | - | - | - |
| 2.8235 | 660 | 0.1324 | - | - | - | - | - |
| 2.8278 | 661 | 0.15 | - | - | - | - | - |
| 2.8321 | 662 | 0.0283 | - | - | - | - | - |
| 2.8364 | 663 | 0.0408 | - | - | - | - | - |
| 2.8406 | 664 | 0.0615 | - | - | - | - | - |
| 2.8449 | 665 | 0.0191 | - | - | - | - | - |
| 2.8492 | 666 | 0.0412 | - | - | - | - | - |
| 2.8535 | 667 | 0.0772 | - | - | - | - | - |
| 2.8578 | 668 | 0.1798 | - | - | - | - | - |
| 2.8620 | 669 | 0.1172 | - | - | - | - | - |
| 2.8663 | 670 | 0.018 | - | - | - | - | - |
| 2.8706 | 671 | 0.0386 | - | - | - | - | - |
| 2.8749 | 672 | 0.1195 | - | - | - | - | - |
| 2.8791 | 673 | 0.0948 | - | - | - | - | - |
| 2.8834 | 674 | 0.0271 | - | - | - | - | - |
| 2.8877 | 675 | 0.0237 | - | - | - | - | - |
| 2.8920 | 676 | 0.0149 | - | - | - | - | - |
| 2.8963 | 677 | 0.0405 | - | - | - | - | - |
| 2.9005 | 678 | 0.0126 | - | - | - | - | - |
| 2.9048 | 679 | 0.0261 | - | - | - | - | - |
| 2.9091 | 680 | 0.0418 | - | - | - | - | - |
| 2.9134 | 681 | 0.0742 | - | - | - | - | - |
| 2.9176 | 682 | 0.0708 | - | - | - | - | - |
| 2.9219 | 683 | 0.1017 | - | - | - | - | - |
| 2.9262 | 684 | 0.0161 | - | - | - | - | - |
| 2.9305 | 685 | 0.0664 | - | - | - | - | - |
| 2.9348 | 686 | 0.0127 | - | - | - | - | - |
| 2.9390 | 687 | 0.0371 | - | - | - | - | - |
| 2.9433 | 688 | 0.0231 | - | - | - | - | - |
| 2.9476 | 689 | 0.0621 | - | - | - | - | - |
| 2.9519 | 690 | 0.1051 | - | - | - | - | - |
| 2.9561 | 691 | 0.4462 | - | - | - | - | - |
| 2.9604 | 692 | 0.1279 | - | - | - | - | - |
| 2.9647 | 693 | 0.0166 | - | - | - | - | - |
| 2.9690 | 694 | 0.0282 | - | - | - | - | - |
| 2.9733 | 695 | 0.014 | - | - | - | - | - |
| 2.9775 | 696 | 0.0428 | - | - | - | - | - |
| 2.9818 | 697 | 0.0319 | - | - | - | - | - |
| 2.9861 | 698 | 0.0031 | - | - | - | - | - |
| 2.9904 | 699 | 0.1171 | - | - | - | - | - |
| 2.9947 | 700 | 0.1301 | - | - | - | - | - |
| 2.9989 | 701 | 0.085 | 0.3525 | 0.3812 | 0.3888 | 0.3093 | 0.3923 |
| 3.0032 | 702 | 0.16 | - | - | - | - | - |
| 3.0075 | 703 | 0.0331 | - | - | - | - | - |
| 3.0118 | 704 | 0.0278 | - | - | - | - | - |
| 3.0160 | 705 | 0.0283 | - | - | - | - | - |
| 3.0203 | 706 | 0.0247 | - | - | - | - | - |
| 3.0246 | 707 | 0.055 | - | - | - | - | - |
| 3.0289 | 708 | 0.1062 | - | - | - | - | - |
| 3.0332 | 709 | 0.0207 | - | - | - | - | - |
| 3.0374 | 710 | 0.0314 | - | - | - | - | - |
| 3.0417 | 711 | 0.0203 | - | - | - | - | - |
| 3.0460 | 712 | 0.1106 | - | - | - | - | - |
| 3.0503 | 713 | 0.0252 | - | - | - | - | - |
| 3.0545 | 714 | 0.0486 | - | - | - | - | - |
| 3.0588 | 715 | 0.0173 | - | - | - | - | - |
| 3.0631 | 716 | 0.0147 | - | - | - | - | - |
| 3.0674 | 717 | 0.0444 | - | - | - | - | - |
| 3.0717 | 718 | 0.0718 | - | - | - | - | - |
| 3.0759 | 719 | 0.0145 | - | - | - | - | - |
| 3.0802 | 720 | 0.2057 | - | - | - | - | - |
| 3.0845 | 721 | 0.0386 | - | - | - | - | - |
| 3.0888 | 722 | 0.0349 | - | - | - | - | - |
| 3.0930 | 723 | 0.0248 | - | - | - | - | - |
| 3.0973 | 724 | 0.0276 | - | - | - | - | - |
| 3.1016 | 725 | 0.0186 | - | - | - | - | - |
| 3.1059 | 726 | 0.1112 | - | - | - | - | - |
| 3.1102 | 727 | 0.0437 | - | - | - | - | - |
| 3.1144 | 728 | 0.0185 | - | - | - | - | - |
| 3.1187 | 729 | 0.0896 | - | - | - | - | - |
| 3.1230 | 730 | 0.2015 | - | - | - | - | - |
| 3.1273 | 731 | 0.0247 | - | - | - | - | - |
| 3.1316 | 732 | 0.0096 | - | - | - | - | - |
| 3.1358 | 733 | 0.0114 | - | - | - | - | - |
| 3.1401 | 734 | 0.1263 | - | - | - | - | - |
| 3.1444 | 735 | 0.0718 | - | - | - | - | - |
| 3.1487 | 736 | 0.0101 | - | - | - | - | - |
| 3.1529 | 737 | 0.125 | - | - | - | - | - |
| 3.1572 | 738 | 0.0931 | - | - | - | - | - |
| 3.1615 | 739 | 0.193 | - | - | - | - | - |
| 3.1658 | 740 | 0.0121 | - | - | - | - | - |
| 3.1701 | 741 | 0.0264 | - | - | - | - | - |
| 3.1743 | 742 | 0.094 | - | - | - | - | - |
| 3.1786 | 743 | 0.0835 | - | - | - | - | - |
| 3.1829 | 744 | 0.031 | - | - | - | - | - |
| 3.1872 | 745 | 0.0297 | - | - | - | - | - |
| 3.1914 | 746 | 0.0416 | - | - | - | - | - |
| 3.1957 | 747 | 0.0173 | - | - | - | - | - |
| 3.2 | 748 | 0.0088 | - | - | - | - | - |
| 3.2043 | 749 | 0.0235 | - | - | - | - | - |
| 3.2086 | 750 | 0.0715 | - | - | - | - | - |
| 3.2128 | 751 | 0.1977 | - | - | - | - | - |
| 3.2171 | 752 | 0.0217 | - | - | - | - | - |
| 3.2214 | 753 | 0.01 | - | - | - | - | - |
| 3.2257 | 754 | 0.016 | - | - | - | - | - |
| 3.2299 | 755 | 0.0116 | - | - | - | - | - |
| 3.2342 | 756 | 0.0662 | - | - | - | - | - |
| 3.2385 | 757 | 0.0783 | - | - | - | - | - |
| 3.2428 | 758 | 0.0814 | - | - | - | - | - |
| 3.2471 | 759 | 0.0391 | - | - | - | - | - |
| 3.2513 | 760 | 0.0329 | - | - | - | - | - |
| 3.2556 | 761 | 0.0238 | - | - | - | - | - |
| 3.2599 | 762 | 0.0124 | - | - | - | - | - |
| 3.2642 | 763 | 0.0529 | - | - | - | - | - |
| 3.2684 | 764 | 0.0735 | - | - | - | - | - |
| 3.2727 | 765 | 0.0444 | - | - | - | - | - |
| 3.2770 | 766 | 0.0489 | - | - | - | - | - |
| 3.2813 | 767 | 0.0074 | - | - | - | - | - |
| 3.2856 | 768 | 0.0149 | - | - | - | - | - |
| 3.2898 | 769 | 0.0147 | - | - | - | - | - |
| 3.2941 | 770 | 0.0235 | - | - | - | - | - |
| 3.2984 | 771 | 0.0224 | - | - | - | - | - |
| 3.3027 | 772 | 0.0231 | - | - | - | - | - |
| 3.3070 | 773 | 0.0049 | - | - | - | - | - |
| 3.3112 | 774 | 0.0166 | - | - | - | - | - |
| 3.3155 | 775 | 0.0259 | - | - | - | - | - |
| 3.3198 | 776 | 0.0373 | - | - | - | - | - |
| 3.3241 | 777 | 0.133 | - | - | - | - | - |
| 3.3283 | 778 | 0.0141 | - | - | - | - | - |
| 3.3326 | 779 | 0.0145 | - | - | - | - | - |
| 3.3369 | 780 | 0.0129 | - | - | - | - | - |
| 3.3412 | 781 | 0.0467 | - | - | - | - | - |
| 3.3455 | 782 | 0.0113 | - | - | - | - | - |
| 3.3497 | 783 | 0.0524 | - | - | - | - | - |
| 3.3540 | 784 | 0.0325 | - | - | - | - | - |
| 3.3583 | 785 | 0.0774 | - | - | - | - | - |
| 3.3626 | 786 | 0.148 | - | - | - | - | - |
| 3.3668 | 787 | 0.0173 | - | - | - | - | - |
| 3.3711 | 788 | 0.0112 | - | - | - | - | - |
| 3.3754 | 789 | 0.0314 | - | - | - | - | - |
| 3.3797 | 790 | 0.0487 | - | - | - | - | - |
| 3.3840 | 791 | 0.0683 | - | - | - | - | - |
| 3.3882 | 792 | 0.0063 | - | - | - | - | - |
| 3.3925 | 793 | 0.0427 | - | - | - | - | - |
| 3.3968 | 794 | 0.0549 | - | - | - | - | - |
| 3.4011 | 795 | 0.0452 | - | - | - | - | - |
| 3.4053 | 796 | 0.0453 | - | - | - | - | - |
| 3.4096 | 797 | 0.0527 | - | - | - | - | - |
| 3.4139 | 798 | 0.234 | - | - | - | - | - |
| 3.4182 | 799 | 0.0263 | - | - | - | - | - |
| 3.4225 | 800 | 0.022 | - | - | - | - | - |
| 3.4267 | 801 | 0.0374 | - | - | - | - | - |
| 3.4310 | 802 | 0.0139 | - | - | - | - | - |
| 3.4353 | 803 | 0.0134 | - | - | - | - | - |
| 3.4396 | 804 | 0.0286 | - | - | - | - | - |
| 3.4439 | 805 | 0.0021 | - | - | - | - | - |
| 3.4481 | 806 | 0.051 | - | - | - | - | - |
| 3.4524 | 807 | 0.2649 | - | - | - | - | - |
| 3.4567 | 808 | 0.0032 | - | - | - | - | - |
| 3.4610 | 809 | 0.0228 | - | - | - | - | - |
| 3.4652 | 810 | 0.0163 | - | - | - | - | - |
| 3.4695 | 811 | 0.0121 | - | - | - | - | - |
| 3.4738 | 812 | 0.0033 | - | - | - | - | - |
| 3.4781 | 813 | 0.0067 | - | - | - | - | - |
| 3.4824 | 814 | 0.0122 | - | - | - | - | - |
| 3.4866 | 815 | 0.0292 | - | - | - | - | - |
| 3.4909 | 816 | 0.0488 | - | - | - | - | - |
| 3.4952 | 817 | 0.025 | - | - | - | - | - |
| 3.4995 | 818 | 0.014 | - | - | - | - | - |
| 3.5037 | 819 | 0.0169 | - | - | - | - | - |
| 3.5080 | 820 | 0.0277 | - | - | - | - | - |
| 3.5123 | 821 | 0.022 | - | - | - | - | - |
| 3.5166 | 822 | 0.0187 | - | - | - | - | - |
| 3.5209 | 823 | 0.0178 | - | - | - | - | - |
| 3.5251 | 824 | 0.0265 | - | - | - | - | - |
| 3.5294 | 825 | 0.0063 | - | - | - | - | - |
| 3.5337 | 826 | 0.0154 | - | - | - | - | - |
| 3.5380 | 827 | 0.0489 | - | - | - | - | - |
| 3.5422 | 828 | 0.029 | - | - | - | - | - |
| 3.5465 | 829 | 0.0496 | - | - | - | - | - |
| 3.5508 | 830 | 0.2485 | - | - | - | - | - |
| 3.5551 | 831 | 0.0394 | - | - | - | - | - |
| 3.5594 | 832 | 0.0294 | - | - | - | - | - |
| 3.5636 | 833 | 0.0262 | - | - | - | - | - |
| 3.5679 | 834 | 0.0368 | - | - | - | - | - |
| 3.5722 | 835 | 0.0163 | - | - | - | - | - |
| 3.5765 | 836 | 0.0167 | - | - | - | - | - |
| 3.5807 | 837 | 0.01 | - | - | - | - | - |
| 3.5850 | 838 | 0.0179 | - | - | - | - | - |
| 3.5893 | 839 | 0.0493 | - | - | - | - | - |
| 3.5936 | 840 | 0.0082 | - | - | - | - | - |
| 3.5979 | 841 | 0.0109 | - | - | - | - | - |
| 3.6021 | 842 | 0.0155 | - | - | - | - | - |
| 3.6064 | 843 | 0.0117 | - | - | - | - | - |
| 3.6107 | 844 | 0.0245 | - | - | - | - | - |
| 3.6150 | 845 | 0.0306 | - | - | - | - | - |
| 3.6193 | 846 | 0.0529 | - | - | - | - | - |
| 3.6235 | 847 | 0.0731 | - | - | - | - | - |
| 3.6278 | 848 | 0.0427 | - | - | - | - | - |
| 3.6321 | 849 | 0.0039 | - | - | - | - | - |
| 3.6364 | 850 | 0.0031 | - | - | - | - | - |
| 3.6406 | 851 | 0.0151 | - | - | - | - | - |
| 3.6449 | 852 | 0.107 | - | - | - | - | - |
| 3.6492 | 853 | 0.1507 | - | - | - | - | - |
| 3.6535 | 854 | 0.0314 | - | - | - | - | - |
| 3.6578 | 855 | 0.0204 | - | - | - | - | - |
| 3.6620 | 856 | 0.0212 | - | - | - | - | - |
| 3.6663 | 857 | 0.0351 | - | - | - | - | - |
| 3.6706 | 858 | 0.0388 | - | - | - | - | - |
| 3.6749 | 859 | 0.0104 | - | - | - | - | - |
| 3.6791 | 860 | 0.0386 | - | - | - | - | - |
| 3.6834 | 861 | 0.0914 | - | - | - | - | - |
| 3.6877 | 862 | 0.0557 | - | - | - | - | - |
| 3.6920 | 863 | 0.021 | - | - | - | - | - |
| 3.6963 | 864 | 0.0176 | - | - | - | - | - |
| 3.7005 | 865 | 0.0064 | - | - | - | - | - |
| 3.7048 | 866 | 0.0292 | - | - | - | - | - |
| 3.7091 | 867 | 0.0663 | - | - | - | - | - |
| 3.7134 | 868 | 0.0363 | - | - | - | - | - |
| 3.7176 | 869 | 0.0759 | - | - | - | - | - |
| 3.7219 | 870 | 0.0693 | - | - | - | - | - |
| 3.7262 | 871 | 0.0369 | - | - | - | - | - |
| 3.7305 | 872 | 0.0396 | - | - | - | - | - |
| 3.7348 | 873 | 0.0389 | - | - | - | - | - |
| 3.7390 | 874 | 0.0331 | - | - | - | - | - |
| 3.7433 | 875 | 0.0344 | - | - | - | - | - |
| 3.7476 | 876 | 0.0155 | - | - | - | - | - |
| 3.7519 | 877 | 0.0213 | - | - | - | - | - |
| 3.7561 | 878 | 0.0939 | - | - | - | - | - |
| 3.7604 | 879 | 0.032 | - | - | - | - | - |
| 3.7647 | 880 | 0.0057 | - | - | - | - | - |
| 3.7690 | 881 | 0.0096 | - | - | - | - | - |
| 3.7733 | 882 | 0.0072 | - | - | - | - | - |
| 3.7775 | 883 | 0.0078 | - | - | - | - | - |
| 3.7818 | 884 | 0.026 | - | - | - | - | - |
| 3.7861 | 885 | 0.0838 | - | - | - | - | - |
| 3.7904 | 886 | 0.0328 | - | - | - | - | - |
| 3.7947 | 887 | 0.0164 | - | - | - | - | - |
| 3.7989 | 888 | 0.0101 | - | - | - | - | - |
| 3.8032 | 889 | 0.0144 | - | - | - | - | - |
| 3.8075 | 890 | 0.0169 | - | - | - | - | - |
| 3.8118 | 891 | 0.0752 | - | - | - | - | - |
| 3.8160 | 892 | 0.1062 | - | - | - | - | - |
| 3.8203 | 893 | 0.0816 | - | - | - | - | - |
| 3.8246 | 894 | 0.0385 | - | - | - | - | - |
| 3.8289 | 895 | 0.0174 | - | - | - | - | - |
| 3.8332 | 896 | 0.0093 | - | - | - | - | - |
| 3.8374 | 897 | 0.0117 | - | - | - | - | - |
| 3.8417 | 898 | 0.0304 | - | - | - | - | - |
| 3.8460 | 899 | 0.0103 | - | - | - | - | - |
| 3.8503 | 900 | 0.0251 | - | - | - | - | - |
| 3.8545 | 901 | 0.0352 | - | - | - | - | - |
| 3.8588 | 902 | 0.0266 | - | - | - | - | - |
| 3.8631 | 903 | 0.0085 | - | - | - | - | - |
| 3.8674 | 904 | 0.0189 | - | - | - | - | - |
| 3.8717 | 905 | 0.0349 | - | - | - | - | - |
| 3.8759 | 906 | 0.037 | - | - | - | - | - |
| 3.8802 | 907 | 0.0215 | - | - | - | - | - |
| 3.8845 | 908 | 0.0113 | - | - | - | - | - |
| 3.8888 | 909 | 0.0063 | - | - | - | - | - |
| 3.8930 | 910 | 0.0102 | - | - | - | - | - |
| 3.8973 | 911 | 0.0108 | - | - | - | - | - |
| 3.9016 | 912 | 0.0059 | - | - | - | - | - |
| 3.9059 | 913 | 0.0373 | - | - | - | - | - |
| 3.9102 | 914 | 0.0147 | - | - | - | - | - |
| 3.9144 | 915 | 0.0508 | - | - | - | - | - |
| 3.9187 | 916 | 0.0297 | - | - | - | - | - |
| 3.9230 | 917 | 0.043 | - | - | - | - | - |
| 3.9273 | 918 | 0.0066 | - | - | - | - | - |
| 3.9316 | 919 | 0.016 | - | - | - | - | - |
| 3.9358 | 920 | 0.0046 | - | - | - | - | - |
| 3.9401 | 921 | 0.0123 | - | - | - | - | - |
| 3.9444 | 922 | 0.0178 | - | - | - | - | - |
| 3.9487 | 923 | 0.044 | - | - | - | - | - |
| 3.9529 | 924 | 0.1045 | - | - | - | - | - |
| 3.9572 | 925 | 0.0353 | - | - | - | - | - |
| 3.9615 | 926 | 0.0692 | - | - | - | - | - |
| 3.9658 | 927 | 0.0108 | - | - | - | - | - |
| 3.9701 | 928 | 0.007 | - | - | - | - | - |
| 3.9743 | 929 | 0.0146 | - | - | - | - | - |
| 3.9786 | 930 | 0.0123 | - | - | - | - | - |
| 3.9829 | 931 | 0.0036 | - | - | - | - | - |
| 3.9872 | 932 | 0.0057 | - | - | - | - | - |
| 3.9914 | 933 | 0.0495 | - | - | - | - | - |
| 3.9957 | 934 | 0.0429 | - | - | - | - | - |
| 4.0 | 935 | 0.0226 | 0.3572 | 0.3768 | 0.3820 | 0.3084 | 0.3844 |
| 4.0043 | 936 | 0.017 | - | - | - | - | - |
| 4.0086 | 937 | 0.0392 | - | - | - | - | - |
| 4.0128 | 938 | 0.0094 | - | - | - | - | - |
| 4.0171 | 939 | 0.01 | - | - | - | - | - |
| 4.0214 | 940 | 0.0086 | - | - | - | - | - |
| 4.0257 | 941 | 0.0226 | - | - | - | - | - |
| 4.0299 | 942 | 0.0263 | - | - | - | - | - |
| 4.0342 | 943 | 0.0089 | - | - | - | - | - |
| 4.0385 | 944 | 0.0059 | - | - | - | - | - |
| 4.0428 | 945 | 0.027 | - | - | - | - | - |
| 4.0471 | 946 | 0.052 | - | - | - | - | - |
| 4.0513 | 947 | 0.0183 | - | - | - | - | - |
| 4.0556 | 948 | 0.0165 | - | - | - | - | - |
| 4.0599 | 949 | 0.0036 | - | - | - | - | - |
| 4.0642 | 950 | 0.0039 | - | - | - | - | - |
| 4.0684 | 951 | 0.0198 | - | - | - | - | - |
| 4.0727 | 952 | 0.0259 | - | - | - | - | - |
| 4.0770 | 953 | 0.0109 | - | - | - | - | - |
| 4.0813 | 954 | 0.091 | - | - | - | - | - |
| 4.0856 | 955 | 0.019 | - | - | - | - | - |
| 4.0898 | 956 | 0.0135 | - | - | - | - | - |
| 4.0941 | 957 | 0.1946 | - | - | - | - | - |
| 4.0984 | 958 | 0.0158 | - | - | - | - | - |
| 4.1027 | 959 | 0.0379 | - | - | - | - | - |
| 4.1070 | 960 | 0.0071 | - | - | - | - | - |
| 4.1112 | 961 | 0.0332 | - | - | - | - | - |
| 4.1155 | 962 | 0.0157 | - | - | - | - | - |
| 4.1198 | 963 | 0.0261 | - | - | - | - | - |
| 4.1241 | 964 | 0.0107 | - | - | - | - | - |
| 4.1283 | 965 | 0.0046 | - | - | - | - | - |
| 4.1326 | 966 | 0.0078 | - | - | - | - | - |
| 4.1369 | 967 | 0.0086 | - | - | - | - | - |
| 4.1412 | 968 | 0.0261 | - | - | - | - | - |
| 4.1455 | 969 | 0.0271 | - | - | - | - | - |
| 4.1497 | 970 | 0.009 | - | - | - | - | - |
| 4.1540 | 971 | 0.0342 | - | - | - | - | - |
| 4.1583 | 972 | 0.0561 | - | - | - | - | - |
| 4.1626 | 973 | 0.0559 | - | - | - | - | - |
| 4.1668 | 974 | 0.024 | - | - | - | - | - |
| 4.1711 | 975 | 0.0083 | - | - | - | - | - |
| 4.1754 | 976 | 0.0757 | - | - | - | - | - |
| 4.1797 | 977 | 0.0353 | - | - | - | - | - |
| 4.1840 | 978 | 0.0135 | - | - | - | - | - |
| 4.1882 | 979 | 0.0681 | - | - | - | - | - |
| 4.1925 | 980 | 0.0132 | - | - | - | - | - |
| 4.1968 | 981 | 0.0104 | - | - | - | - | - |
| 4.2011 | 982 | 0.0191 | - | - | - | - | - |
| 4.2053 | 983 | 0.0684 | - | - | - | - | - |
| 4.2096 | 984 | 0.0176 | - | - | - | - | - |
| 4.2139 | 985 | 0.0193 | - | - | - | - | - |
| 4.2182 | 986 | 0.0105 | - | - | - | - | - |
| 4.2225 | 987 | 0.0057 | - | - | - | - | - |
| 4.2267 | 988 | 0.0069 | - | - | - | - | - |
| 4.2310 | 989 | 0.0237 | - | - | - | - | - |
| 4.2353 | 990 | 0.0571 | - | - | - | - | - |
| 4.2396 | 991 | 0.0182 | - | - | - | - | - |
| 4.2439 | 992 | 0.0093 | - | - | - | - | - |
| 4.2481 | 993 | 0.0366 | - | - | - | - | - |
| 4.2524 | 994 | 0.0132 | - | - | - | - | - |
| 4.2567 | 995 | 0.0192 | - | - | - | - | - |
| 4.2610 | 996 | 0.0127 | - | - | - | - | - |
| 4.2652 | 997 | 0.0067 | - | - | - | - | - |
| 4.2695 | 998 | 0.0228 | - | - | - | - | - |
| 4.2738 | 999 | 0.0212 | - | - | - | - | - |
| 4.2781 | 1000 | 0.0061 | - | - | - | - | - |
| 4.2824 | 1001 | 0.0057 | - | - | - | - | - |
| 4.2866 | 1002 | 0.0037 | - | - | - | - | - |
| 4.2909 | 1003 | 0.0108 | - | - | - | - | - |
| 4.2952 | 1004 | 0.0089 | - | - | - | - | - |
| 4.2995 | 1005 | 0.013 | - | - | - | - | - |
| 4.3037 | 1006 | 0.0157 | - | - | - | - | - |
| 4.3080 | 1007 | 0.0101 | - | - | - | - | - |
| 4.3123 | 1008 | 0.0032 | - | - | - | - | - |
| 4.3166 | 1009 | 0.0151 | - | - | - | - | - |
| 4.3209 | 1010 | 0.0287 | - | - | - | - | - |
| 4.3251 | 1011 | 0.0192 | - | - | - | - | - |
| 4.3294 | 1012 | 0.0124 | - | - | - | - | - |
| 4.3337 | 1013 | 0.0035 | - | - | - | - | - |
| 4.3380 | 1014 | 0.0091 | - | - | - | - | - |
| 4.3422 | 1015 | 0.0477 | - | - | - | - | - |
| 4.3465 | 1016 | 0.0042 | - | - | - | - | - |
| 4.3508 | 1017 | 0.0133 | - | - | - | - | - |
| 4.3551 | 1018 | 0.013 | - | - | - | - | - |
| 4.3594 | 1019 | 0.0302 | - | - | - | - | - |
| 4.3636 | 1020 | 0.0072 | - | - | - | - | - |
| 4.3679 | 1021 | 0.011 | - | - | - | - | - |
| 4.3722 | 1022 | 0.0165 | - | - | - | - | - |
| 4.3765 | 1023 | 0.0259 | - | - | - | - | - |
| 4.3807 | 1024 | 0.0101 | - | - | - | - | - |
| 4.3850 | 1025 | 0.0132 | - | - | - | - | - |
| 4.3893 | 1026 | 0.0134 | - | - | - | - | - |
| 4.3936 | 1027 | 0.0365 | - | - | - | - | - |
| 4.3979 | 1028 | 0.0314 | - | - | - | - | - |
| 4.4021 | 1029 | 0.02 | - | - | - | - | - |
| 4.4064 | 1030 | 0.009 | - | - | - | - | - |
| 4.4107 | 1031 | 0.021 | - | - | - | - | - |
| 4.4150 | 1032 | 0.031 | - | - | - | - | - |
| 4.4193 | 1033 | 0.0116 | - | - | - | - | - |
| 4.4235 | 1034 | 0.0126 | - | - | - | - | - |
| 4.4278 | 1035 | 0.0171 | - | - | - | - | - |
| 4.4321 | 1036 | 0.0084 | - | - | - | - | - |
| 4.4364 | 1037 | 0.0101 | - | - | - | - | - |
| 4.4406 | 1038 | 0.0116 | - | - | - | - | - |
| 4.4449 | 1039 | 0.0131 | - | - | - | - | - |
| 4.4492 | 1040 | 0.0513 | - | - | - | - | - |
| 4.4535 | 1041 | 0.0487 | - | - | - | - | - |
| 4.4578 | 1042 | 0.0034 | - | - | - | - | - |
| 4.4620 | 1043 | 0.0036 | - | - | - | - | - |
| 4.4663 | 1044 | 0.0173 | - | - | - | - | - |
| 4.4706 | 1045 | 0.0071 | - | - | - | - | - |
| 4.4749 | 1046 | 0.0019 | - | - | - | - | - |
| 4.4791 | 1047 | 0.0171 | - | - | - | - | - |
| 4.4834 | 1048 | 0.0044 | - | - | - | - | - |
| 4.4877 | 1049 | 0.0397 | - | - | - | - | - |
| 4.4920 | 1050 | 0.0827 | - | - | - | - | - |
| 4.4963 | 1051 | 0.0148 | - | - | - | - | - |
| 4.5005 | 1052 | 0.0054 | - | - | - | - | - |
| 4.5048 | 1053 | 0.0141 | - | - | - | - | - |
| 4.5091 | 1054 | 0.0233 | - | - | - | - | - |
| 4.5134 | 1055 | 0.0088 | - | - | - | - | - |
| 4.5176 | 1056 | 0.0034 | - | - | - | - | - |
| 4.5219 | 1057 | 0.0145 | - | - | - | - | - |
| 4.5262 | 1058 | 0.0456 | - | - | - | - | - |
| 4.5305 | 1059 | 0.0051 | - | - | - | - | - |
| 4.5348 | 1060 | 0.0106 | - | - | - | - | - |
| 4.5390 | 1061 | 0.0114 | - | - | - | - | - |
| 4.5433 | 1062 | 0.0105 | - | - | - | - | - |
| 4.5476 | 1063 | 0.041 | - | - | - | - | - |
| 4.5519 | 1064 | 0.0776 | - | - | - | - | - |
| 4.5561 | 1065 | 0.0055 | - | - | - | - | - |
| 4.5604 | 1066 | 0.0139 | - | - | - | - | - |
| 4.5647 | 1067 | 0.0246 | - | - | - | - | - |
| 4.5690 | 1068 | 0.0127 | - | - | - | - | - |
| 4.5733 | 1069 | 0.0084 | - | - | - | - | - |
| 4.5775 | 1070 | 0.0157 | - | - | - | - | - |
| 4.5818 | 1071 | 0.0086 | - | - | - | - | - |
| 4.5861 | 1072 | 0.0129 | - | - | - | - | - |
| 4.5904 | 1073 | 0.0111 | - | - | - | - | - |
| 4.5947 | 1074 | 0.0069 | - | - | - | - | - |
| 4.5989 | 1075 | 0.006 | - | - | - | - | - |
| 4.6032 | 1076 | 0.0099 | - | - | - | - | - |
| 4.6075 | 1077 | 0.0459 | - | - | - | - | - |
| 4.6118 | 1078 | 0.0332 | - | - | - | - | - |
| 4.6160 | 1079 | 0.0317 | - | - | - | - | - |
| 4.6203 | 1080 | 0.0444 | - | - | - | - | - |
| 4.6246 | 1081 | 0.0416 | - | - | - | - | - |
| 4.6289 | 1082 | 0.0022 | - | - | - | - | - |
| 4.6332 | 1083 | 0.0023 | - | - | - | - | - |
| 4.6374 | 1084 | 0.004 | - | - | - | - | - |
| 4.6417 | 1085 | 0.0127 | - | - | - | - | - |
| 4.6460 | 1086 | 0.0664 | - | - | - | - | - |
| 4.6503 | 1087 | 0.0348 | - | - | - | - | - |
| 4.6545 | 1088 | 0.0384 | - | - | - | - | - |
| 4.6588 | 1089 | 0.0067 | - | - | - | - | - |
| 4.6631 | 1090 | 0.0136 | - | - | - | - | - |
| 4.6674 | 1091 | 0.0095 | - | - | - | - | - |
| 4.6717 | 1092 | 0.0178 | - | - | - | - | - |
| 4.6759 | 1093 | 0.0073 | - | - | - | - | - |
| 4.6802 | 1094 | 0.0435 | - | - | - | - | - |
| 4.6845 | 1095 | 0.0158 | - | - | - | - | - |
| 4.6888 | 1096 | 0.0291 | - | - | - | - | - |
| 4.6930 | 1097 | 0.0087 | - | - | - | - | - |
| 4.6973 | 1098 | 0.0152 | - | - | - | - | - |
| 4.7016 | 1099 | 0.0118 | - | - | - | - | - |
| 4.7059 | 1100 | 0.0282 | - | - | - | - | - |
| 4.7102 | 1101 | 0.085 | - | - | - | - | - |
| 4.7144 | 1102 | 0.0545 | - | - | - | - | - |
| 4.7187 | 1103 | 0.0135 | - | - | - | - | - |
| 4.7230 | 1104 | 0.0586 | - | - | - | - | - |
| 4.7273 | 1105 | 0.0332 | - | - | - | - | - |
| 4.7316 | 1106 | 0.012 | - | - | - | - | - |
| 4.7358 | 1107 | 0.0268 | - | - | - | - | - |
| 4.7401 | 1108 | 0.0208 | - | - | - | - | - |
| 4.7444 | 1109 | 0.04 | - | - | - | - | - |
| 4.7487 | 1110 | 0.0072 | - | - | - | - | - |
| 4.7529 | 1111 | 0.0238 | - | - | - | - | - |
| 4.7572 | 1112 | 0.0267 | - | - | - | - | - |
| 4.7615 | 1113 | 0.0091 | - | - | - | - | - |
| 4.7658 | 1114 | 0.0057 | - | - | - | - | - |
| 4.7701 | 1115 | 0.0045 | - | - | - | - | - |
| 4.7743 | 1116 | 0.0064 | - | - | - | - | - |
| 4.7786 | 1117 | 0.0109 | - | - | - | - | - |
| 4.7829 | 1118 | 0.0115 | - | - | - | - | - |
| 4.7872 | 1119 | 0.0308 | - | - | - | - | - |
| 4.7914 | 1120 | 0.0183 | - | - | - | - | - |
| 4.7957 | 1121 | 0.0106 | - | - | - | - | - |
| 4.8 | 1122 | 0.0085 | - | - | - | - | - |
| 4.8043 | 1123 | 0.0114 | - | - | - | - | - |
| 4.8086 | 1124 | 0.0088 | - | - | - | - | - |
| 4.8128 | 1125 | 0.0139 | - | - | - | - | - |
| 4.8171 | 1126 | 0.0688 | - | - | - | - | - |
| 4.8214 | 1127 | 0.0323 | - | - | - | - | - |
| 4.8257 | 1128 | 0.0226 | - | - | - | - | - |
| 4.8299 | 1129 | 0.0144 | - | - | - | - | - |
| 4.8342 | 1130 | 0.0043 | - | - | - | - | - |
| 4.8385 | 1131 | 0.0064 | - | - | - | - | - |
| 4.8428 | 1132 | 0.0357 | - | - | - | - | - |
| 4.8471 | 1133 | 0.0212 | - | - | - | - | - |
| 4.8513 | 1134 | 0.0231 | - | - | - | - | - |
| 4.8556 | 1135 | 0.0326 | - | - | - | - | - |
| 4.8599 | 1136 | 0.0153 | - | - | - | - | - |
| 4.8642 | 1137 | 0.0064 | - | - | - | - | - |
| 4.8684 | 1138 | 0.0134 | - | - | - | - | - |
| 4.8727 | 1139 | 0.0242 | - | - | - | - | - |
| 4.8770 | 1140 | 0.0774 | - | - | - | - | - |
| 4.8813 | 1141 | 0.023 | - | - | - | - | - |
| 4.8856 | 1142 | 0.0066 | - | - | - | - | - |
| 4.8898 | 1143 | 0.0063 | - | - | - | - | - |
| 4.8941 | 1144 | 0.0054 | - | - | - | - | - |
| 4.8984 | 1145 | 0.0079 | - | - | - | - | - |
| 4.9027 | 1146 | 0.0064 | - | - | - | - | - |
| 4.9070 | 1147 | 0.0125 | - | - | - | - | - |
| 4.9112 | 1148 | 0.0134 | - | - | - | - | - |
| 4.9155 | 1149 | 0.0185 | - | - | - | - | - |
| 4.9198 | 1150 | 0.0152 | - | - | - | - | - |
| 4.9241 | 1151 | 0.0116 | - | - | - | - | - |
| 4.9283 | 1152 | 0.0103 | - | - | - | - | - |
| 4.9326 | 1153 | 0.005 | - | - | - | - | - |
| 4.9369 | 1154 | 0.0047 | - | - | - | - | - |
| 4.9412 | 1155 | 0.0227 | - | - | - | - | - |
| 4.9455 | 1156 | 0.0225 | - | - | - | - | - |
| 4.9497 | 1157 | 0.0084 | - | - | - | - | - |
| 4.9540 | 1158 | 0.0819 | - | - | - | - | - |
| 4.9583 | 1159 | 0.0198 | - | - | - | - | - |
| 4.9626 | 1160 | 0.0204 | - | - | - | - | - |
| 4.9668 | 1161 | 0.0043 | - | - | - | - | - |
| 4.9711 | 1162 | 0.037 | - | - | - | - | - |
| 4.9754 | 1163 | 0.0128 | - | - | - | - | - |
| 4.9797 | 1164 | 0.0061 | - | - | - | - | - |
| 4.9840 | 1165 | 0.0064 | 0.3517 | 0.3731 | 0.3808 | 0.3068 | 0.3898 |
* The bold row denotes the saved checkpoint.
</details>
### Framework Versions
- Python: 3.12.2
- Sentence Transformers: 3.0.0
- Transformers: 4.41.2
- PyTorch: 2.3.1
- Accelerate: 0.27.2
- Datasets: 2.19.1
- Tokenizers: 0.19.1
## 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",
}
```
#### MatryoshkaLoss
```bibtex
@misc{kusupati2024matryoshka,
title={Matryoshka Representation Learning},
author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
year={2024},
eprint={2205.13147},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
#### MultipleNegativesRankingLoss
```bibtex
@misc{henderson2017efficient,
title={Efficient Natural Language Response Suggestion for Smart Reply},
author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
year={2017},
eprint={1705.00652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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