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---
base_model: microsoft/deberta-v3-small
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spearman_euclidean
- pearson_dot
- spearman_dot
- pearson_max
- spearman_max
- cosine_accuracy
- cosine_accuracy_threshold
- cosine_f1
- cosine_f1_threshold
- cosine_precision
- cosine_recall
- cosine_ap
- dot_accuracy
- dot_accuracy_threshold
- dot_f1
- dot_f1_threshold
- dot_precision
- dot_recall
- dot_ap
- manhattan_accuracy
- manhattan_accuracy_threshold
- manhattan_f1
- manhattan_f1_threshold
- manhattan_precision
- manhattan_recall
- manhattan_ap
- euclidean_accuracy
- euclidean_accuracy_threshold
- euclidean_f1
- euclidean_f1_threshold
- euclidean_precision
- euclidean_recall
- euclidean_ap
- max_accuracy
- max_accuracy_threshold
- max_f1
- max_f1_threshold
- max_precision
- max_recall
- max_ap
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:32500
- loss:GISTEmbedLoss
widget:
- source_sentence: phase changes do not change
sentences:
- The major Atlantic slave trading nations, ordered by trade volume, were the Portuguese,
the British, the Spanish, the French, the Dutch, and the Danish. Several had established
outposts on the African coast where they purchased slaves from local African leaders.
- "phase changes do not change mass. Particles have mass, but mass is energy. \n\
\ phase changes do not change energy"
- According to the U.S. Census Bureau , the county is a total area of , which has
land and ( 0.2 % ) is water .
- source_sentence: what jobs can you get with a bachelor degree in anthropology?
sentences:
- To determine the atomic weight of an element, you should add up protons and neutrons.
- '[''Paleontologist*'', ''Archaeologist*'', ''University Professor*'', ''Market
Research Analyst*'', ''Primatologist.'', ''Forensic Scientist*'', ''Medical Anthropologist.'',
''Museum Technician.'']'
- The wingspan flies , the moth comes depending on the location from July to August
.
- source_sentence: Identify different forms of energy (e.g., light, sound, heat).
sentences:
- '`` Irreplaceable '''' '''' remained on the chart for thirty weeks , and was certified
double-platinum by the Recording Industry Association of America ( RIAA ) , denoting
sales of two million downloads , and had sold over 3,139,000 paid digital downloads
in the US as of October 2012 , according to Nielsen SoundScan . '''''
- On Rotten Tomatoes , the film has a rating of 63 % , based on 87 reviews , with
an average rating of 5.9/10 .
- Heat, light, and sound are all different forms of energy.
- source_sentence: what is so small it can only be seen with an electron microscope?
sentences:
- "Viruses are so small that they can be seen only with an electron microscope..\
\ Where most viruses are DNA, HIV is an RNA virus. \n HIV is so small it can only\
\ be seen with an electron microscope"
- The development of modern lasers has opened many doors to both research and applications.
A laser beam was used to measure the distance from the Earth to the moon. Lasers
are important components of CD players. As the image above illustrates, lasers
can provide precise focusing of beams to selectively destroy cancer cells in patients.
The ability of a laser to focus precisely is due to high-quality crystals that
help give rise to the laser beam. A variety of techniques are used to manufacture
pure crystals for use in lasers.
- Discussion for (a) This value is the net work done on the package. The person
actually does more work than this, because friction opposes the motion. Friction
does negative work and removes some of the energy the person expends and converts
it to thermal energy. The net work equals the sum of the work done by each individual
force. Strategy and Concept for (b) The forces acting on the package are gravity,
the normal force, the force of friction, and the applied force. The normal force
and force of gravity are each perpendicular to the displacement, and therefore
do no work. Solution for (b) The applied force does work.
- source_sentence: what aspects of your environment may relate to the epidemic of
obesity
sentences:
- Jan Kromkamp ( born August 17 , 1980 in Makkinga , Netherlands ) is a Dutch footballer
.
- When chemicals in solution react, the proper way of writing the chemical formulas
of the dissolved ionic compounds is in terms of the dissociated ions, not the
complete ionic formula. A complete ionic equation is a chemical equation in which
the dissolved ionic compounds are written as separated ions. Solubility rules
are very useful in determining which ionic compounds are dissolved and which are
not. For example, when NaCl(aq) reacts with AgNO3(aq) in a double-replacement
reaction to precipitate AgCl(s) and form NaNO3(aq), the complete ionic equation
includes NaCl, AgNO3, and NaNO3 written as separated ions:.
- Genetic changes in human populations occur too slowly to be responsible for the
obesity epidemic. Nevertheless, the variation in how people respond to the environment
that promotes physical inactivity and intake of high-calorie foods suggests that
genes do play a role in the development of obesity.
model-index:
- name: SentenceTransformer based on microsoft/deberta-v3-small
results:
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: sts test
type: sts-test
metrics:
- type: pearson_cosine
value: 0.6261543137722272
name: Pearson Cosine
- type: spearman_cosine
value: 0.6380566379755814
name: Spearman Cosine
- type: pearson_manhattan
value: 0.64545238834986
name: Pearson Manhattan
- type: spearman_manhattan
value: 0.638675279413056
name: Spearman Manhattan
- type: pearson_euclidean
value: 0.6433597379437007
name: Pearson Euclidean
- type: spearman_euclidean
value: 0.6380140347747367
name: Spearman Euclidean
- type: pearson_dot
value: 0.6259993945400585
name: Pearson Dot
- type: spearman_dot
value: 0.6378358352518761
name: Spearman Dot
- type: pearson_max
value: 0.64545238834986
name: Pearson Max
- type: spearman_max
value: 0.638675279413056
name: Spearman Max
- task:
type: binary-classification
name: Binary Classification
dataset:
name: allNLI dev
type: allNLI-dev
metrics:
- type: cosine_accuracy
value: 0.6796875
name: Cosine Accuracy
- type: cosine_accuracy_threshold
value: 0.9540110230445862
name: Cosine Accuracy Threshold
- type: cosine_f1
value: 0.5454545454545455
name: Cosine F1
- type: cosine_f1_threshold
value: 0.8630210161209106
name: Cosine F1 Threshold
- type: cosine_precision
value: 0.44244604316546765
name: Cosine Precision
- type: cosine_recall
value: 0.7109826589595376
name: Cosine Recall
- type: cosine_ap
value: 0.4867883737362577
name: Cosine Ap
- type: dot_accuracy
value: 0.6796875
name: Dot Accuracy
- type: dot_accuracy_threshold
value: 733.4241943359375
name: Dot Accuracy Threshold
- type: dot_f1
value: 0.5454545454545455
name: Dot F1
- type: dot_f1_threshold
value: 663.4332885742188
name: Dot F1 Threshold
- type: dot_precision
value: 0.44244604316546765
name: Dot Precision
- type: dot_recall
value: 0.7109826589595376
name: Dot Recall
- type: dot_ap
value: 0.4866316260057906
name: Dot Ap
- type: manhattan_accuracy
value: 0.677734375
name: Manhattan Accuracy
- type: manhattan_accuracy_threshold
value: 181.60472106933594
name: Manhattan Accuracy Threshold
- type: manhattan_f1
value: 0.550537634408602
name: Manhattan F1
- type: manhattan_f1_threshold
value: 319.623046875
name: Manhattan F1 Threshold
- type: manhattan_precision
value: 0.4383561643835616
name: Manhattan Precision
- type: manhattan_recall
value: 0.7398843930635838
name: Manhattan Recall
- type: manhattan_ap
value: 0.4882823795400136
name: Manhattan Ap
- type: euclidean_accuracy
value: 0.6796875
name: Euclidean Accuracy
- type: euclidean_accuracy_threshold
value: 8.408852577209473
name: Euclidean Accuracy Threshold
- type: euclidean_f1
value: 0.5454545454545455
name: Euclidean F1
- type: euclidean_f1_threshold
value: 14.51208782196045
name: Euclidean F1 Threshold
- type: euclidean_precision
value: 0.44244604316546765
name: Euclidean Precision
- type: euclidean_recall
value: 0.7109826589595376
name: Euclidean Recall
- type: euclidean_ap
value: 0.48671939529879626
name: Euclidean Ap
- type: max_accuracy
value: 0.6796875
name: Max Accuracy
- type: max_accuracy_threshold
value: 733.4241943359375
name: Max Accuracy Threshold
- type: max_f1
value: 0.550537634408602
name: Max F1
- type: max_f1_threshold
value: 663.4332885742188
name: Max F1 Threshold
- type: max_precision
value: 0.44244604316546765
name: Max Precision
- type: max_recall
value: 0.7398843930635838
name: Max Recall
- type: max_ap
value: 0.4882823795400136
name: Max Ap
- task:
type: binary-classification
name: Binary Classification
dataset:
name: Qnli dev
type: Qnli-dev
metrics:
- type: cosine_accuracy
value: 0.666015625
name: Cosine Accuracy
- type: cosine_accuracy_threshold
value: 0.8842042684555054
name: Cosine Accuracy Threshold
- type: cosine_f1
value: 0.6793103448275861
name: Cosine F1
- type: cosine_f1_threshold
value: 0.8030812740325928
name: Cosine F1 Threshold
- type: cosine_precision
value: 0.5726744186046512
name: Cosine Precision
- type: cosine_recall
value: 0.8347457627118644
name: Cosine Recall
- type: cosine_ap
value: 0.7052019976296955
name: Cosine Ap
- type: dot_accuracy
value: 0.66796875
name: Dot Accuracy
- type: dot_accuracy_threshold
value: 679.375244140625
name: Dot Accuracy Threshold
- type: dot_f1
value: 0.6794425087108014
name: Dot F1
- type: dot_f1_threshold
value: 618.5501708984375
name: Dot F1 Threshold
- type: dot_precision
value: 0.5769230769230769
name: Dot Precision
- type: dot_recall
value: 0.826271186440678
name: Dot Recall
- type: dot_ap
value: 0.7054354866961744
name: Dot Ap
- type: manhattan_accuracy
value: 0.669921875
name: Manhattan Accuracy
- type: manhattan_accuracy_threshold
value: 288.81317138671875
name: Manhattan Accuracy Threshold
- type: manhattan_f1
value: 0.6791862284820032
name: Manhattan F1
- type: manhattan_f1_threshold
value: 405.0858459472656
name: Manhattan F1 Threshold
- type: manhattan_precision
value: 0.5384615384615384
name: Manhattan Precision
- type: manhattan_recall
value: 0.9194915254237288
name: Manhattan Recall
- type: manhattan_ap
value: 0.7053588266129154
name: Manhattan Ap
- type: euclidean_accuracy
value: 0.666015625
name: Euclidean Accuracy
- type: euclidean_accuracy_threshold
value: 13.342350006103516
name: Euclidean Accuracy Threshold
- type: euclidean_f1
value: 0.6793103448275861
name: Euclidean F1
- type: euclidean_f1_threshold
value: 17.398447036743164
name: Euclidean F1 Threshold
- type: euclidean_precision
value: 0.5726744186046512
name: Euclidean Precision
- type: euclidean_recall
value: 0.8347457627118644
name: Euclidean Recall
- type: euclidean_ap
value: 0.7052194558904903
name: Euclidean Ap
- type: max_accuracy
value: 0.669921875
name: Max Accuracy
- type: max_accuracy_threshold
value: 679.375244140625
name: Max Accuracy Threshold
- type: max_f1
value: 0.6794425087108014
name: Max F1
- type: max_f1_threshold
value: 618.5501708984375
name: Max F1 Threshold
- type: max_precision
value: 0.5769230769230769
name: Max Precision
- type: max_recall
value: 0.9194915254237288
name: Max Recall
- type: max_ap
value: 0.7054354866961744
name: Max Ap
---
# SentenceTransformer based on microsoft/deberta-v3-small
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small). 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:** [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) <!-- at revision a36c739020e01763fe789b4b85e2df55d6180012 -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### 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': 512, 'do_lower_case': False}) with Transformer model: DebertaV2Model
(1): AdvancedWeightedPooling(
(alpha_dropout_layer): Dropout(p=0.05, inplace=False)
(gate_dropout_layer): Dropout(p=0.0, inplace=False)
(linear_cls_Qpj): Linear(in_features=768, out_features=768, bias=True)
(linear_attnOut): Linear(in_features=768, out_features=768, bias=True)
(mha): MultiheadAttention(
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)
)
(layernorm_output): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
(layernorm_weightedPooing): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
(layernorm_attnOut): LayerNorm((768,), eps=1e-05, elementwise_affine=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("bobox/DeBERTa3-s-CustomPoolin-toytest4-step1-checkpoints-tmp")
# Run inference
sentences = [
'what aspects of your environment may relate to the epidemic of obesity',
'Genetic changes in human populations occur too slowly to be responsible for the obesity epidemic. Nevertheless, the variation in how people respond to the environment that promotes physical inactivity and intake of high-calorie foods suggests that genes do play a role in the development of obesity.',
'When chemicals in solution react, the proper way of writing the chemical formulas of the dissolved ionic compounds is in terms of the dissociated ions, not the complete ionic formula. A complete ionic equation is a chemical equation in which the dissolved ionic compounds are written as separated ions. Solubility rules are very useful in determining which ionic compounds are dissolved and which are not. For example, when NaCl(aq) reacts with AgNO3(aq) in a double-replacement reaction to precipitate AgCl(s) and form NaNO3(aq), the complete ionic equation includes NaCl, AgNO3, and NaNO3 written as separated ions:.',
]
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
#### Semantic Similarity
* Dataset: `sts-test`
* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| pearson_cosine | 0.6262 |
| **spearman_cosine** | **0.6381** |
| pearson_manhattan | 0.6455 |
| spearman_manhattan | 0.6387 |
| pearson_euclidean | 0.6434 |
| spearman_euclidean | 0.638 |
| pearson_dot | 0.626 |
| spearman_dot | 0.6378 |
| pearson_max | 0.6455 |
| spearman_max | 0.6387 |
#### Binary Classification
* Dataset: `allNLI-dev`
* Evaluated with [<code>BinaryClassificationEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator)
| Metric | Value |
|:-----------------------------|:-----------|
| cosine_accuracy | 0.6797 |
| cosine_accuracy_threshold | 0.954 |
| cosine_f1 | 0.5455 |
| cosine_f1_threshold | 0.863 |
| cosine_precision | 0.4424 |
| cosine_recall | 0.711 |
| cosine_ap | 0.4868 |
| dot_accuracy | 0.6797 |
| dot_accuracy_threshold | 733.4242 |
| dot_f1 | 0.5455 |
| dot_f1_threshold | 663.4333 |
| dot_precision | 0.4424 |
| dot_recall | 0.711 |
| dot_ap | 0.4866 |
| manhattan_accuracy | 0.6777 |
| manhattan_accuracy_threshold | 181.6047 |
| manhattan_f1 | 0.5505 |
| manhattan_f1_threshold | 319.623 |
| manhattan_precision | 0.4384 |
| manhattan_recall | 0.7399 |
| manhattan_ap | 0.4883 |
| euclidean_accuracy | 0.6797 |
| euclidean_accuracy_threshold | 8.4089 |
| euclidean_f1 | 0.5455 |
| euclidean_f1_threshold | 14.5121 |
| euclidean_precision | 0.4424 |
| euclidean_recall | 0.711 |
| euclidean_ap | 0.4867 |
| max_accuracy | 0.6797 |
| max_accuracy_threshold | 733.4242 |
| max_f1 | 0.5505 |
| max_f1_threshold | 663.4333 |
| max_precision | 0.4424 |
| max_recall | 0.7399 |
| **max_ap** | **0.4883** |
#### Binary Classification
* Dataset: `Qnli-dev`
* Evaluated with [<code>BinaryClassificationEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator)
| Metric | Value |
|:-----------------------------|:-----------|
| cosine_accuracy | 0.666 |
| cosine_accuracy_threshold | 0.8842 |
| cosine_f1 | 0.6793 |
| cosine_f1_threshold | 0.8031 |
| cosine_precision | 0.5727 |
| cosine_recall | 0.8347 |
| cosine_ap | 0.7052 |
| dot_accuracy | 0.668 |
| dot_accuracy_threshold | 679.3752 |
| dot_f1 | 0.6794 |
| dot_f1_threshold | 618.5502 |
| dot_precision | 0.5769 |
| dot_recall | 0.8263 |
| dot_ap | 0.7054 |
| manhattan_accuracy | 0.6699 |
| manhattan_accuracy_threshold | 288.8132 |
| manhattan_f1 | 0.6792 |
| manhattan_f1_threshold | 405.0858 |
| manhattan_precision | 0.5385 |
| manhattan_recall | 0.9195 |
| manhattan_ap | 0.7054 |
| euclidean_accuracy | 0.666 |
| euclidean_accuracy_threshold | 13.3424 |
| euclidean_f1 | 0.6793 |
| euclidean_f1_threshold | 17.3984 |
| euclidean_precision | 0.5727 |
| euclidean_recall | 0.8347 |
| euclidean_ap | 0.7052 |
| max_accuracy | 0.6699 |
| max_accuracy_threshold | 679.3752 |
| max_f1 | 0.6794 |
| max_f1_threshold | 618.5502 |
| max_precision | 0.5769 |
| max_recall | 0.9195 |
| **max_ap** | **0.7054** |
<!--
## 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: 32,500 training samples
* Columns: <code>sentence1</code> and <code>sentence2</code>
* Approximate statistics based on the first 1000 samples:
| | sentence1 | sentence2 |
|:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 4 tokens</li><li>mean: 29.39 tokens</li><li>max: 323 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 54.42 tokens</li><li>max: 423 tokens</li></ul> |
* Samples:
| sentence1 | sentence2 |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>In which London road is Harrod’s department store?</code> | <code>Harrods, Brompton Road, London | Shopping/Department Stores in London | LondonTown.com Opening Times Britain's most famous store and possibly the most famous store in the world, Harrods features on many tourist 'must-see' lists - and with good reason. Its humble beginnings date back to 1849, when Charles Henry Harrod opened a small East End grocer and tea merchant business that emphasised impeccable service over value. Today, it occupies a vast seven floor site in London's fashionable Knightsbridge and boasts a phenomenal range of products from pianos and cooking pans to fashion and perfumery. The luxurious Urban Retreat can be found on the sixth floor while newer departments include Superbrands, with 17 boutiques from top international designers, and Salon du Parfums, housing some of the most exceptional and exclusive perfumes in the world. The Food Hall is ostentatious to the core and mouth-wateringly exotic, and the store as a whole is well served with 27 restaurants. At Christmas time the Brompton Road windows are transformed into a magical winter wonderland and Father Christmas takes up residence at the enchanting Christmas Grotto. The summer and winter sales are calendar events in the shopping year, and although both sales are extremely crowded there are some great bargains on offer. �</code> |
| <code>e.&#9;in solids the atoms are closely locked in position and can only vibrate, in liquids the atoms and molecules are more loosely connected and can collide with and move past one another, while in gases the atoms or molecules are free to move independently, colliding frequently.</code> | <code>Within a substance, atoms that collide frequently and move independently of one another are most likely in a gas</code> |
| <code>Joe Cole was unable to join West Bromwich Albion .</code> | <code>On 16th October Joe Cole took a long hard look at himself realising that he would never get the opportunity to join West Bromwich Albion and joined Coventry City instead.</code> |
* Loss: [<code>GISTEmbedLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#gistembedloss) with these parameters:
```json
{'guide': SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
(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})
(2): Normalize()
), 'temperature': 0.025}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 256
- `lr_scheduler_type`: cosine_with_min_lr
- `lr_scheduler_kwargs`: {'num_cycles': 0.5, 'min_lr': 3.3333333333333337e-06}
- `warmup_ratio`: 0.33
- `save_safetensors`: False
- `fp16`: True
- `push_to_hub`: True
- `hub_model_id`: bobox/DeBERTa3-s-CustomPoolin-toytest4-step1-checkpoints-tmp
- `hub_strategy`: all_checkpoints
- `batch_sampler`: no_duplicates
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 256
- `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`: 3
- `max_steps`: -1
- `lr_scheduler_type`: cosine_with_min_lr
- `lr_scheduler_kwargs`: {'num_cycles': 0.5, 'min_lr': 3.3333333333333337e-06}
- `warmup_ratio`: 0.33
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: False
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: True
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `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`: True
- `resume_from_checkpoint`: None
- `hub_model_id`: bobox/DeBERTa3-s-CustomPoolin-toytest4-step1-checkpoints-tmp
- `hub_strategy`: all_checkpoints
- `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
- `eval_on_start`: False
- `eval_use_gather_object`: False
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
<details><summary>Click to expand</summary>
| Epoch | Step | Training Loss | sts-test_spearman_cosine | allNLI-dev_max_ap | Qnli-dev_max_ap |
|:------:|:----:|:-------------:|:------------------------:|:-----------------:|:---------------:|
| 0.0010 | 1 | 6.0688 | - | - | - |
| 0.0020 | 2 | 7.5576 | - | - | - |
| 0.0030 | 3 | 4.6849 | - | - | - |
| 0.0039 | 4 | 5.4503 | - | - | - |
| 0.0049 | 5 | 5.6057 | - | - | - |
| 0.0059 | 6 | 6.3049 | - | - | - |
| 0.0069 | 7 | 6.8336 | - | - | - |
| 0.0079 | 8 | 5.0777 | - | - | - |
| 0.0089 | 9 | 4.8358 | - | - | - |
| 0.0098 | 10 | 4.641 | - | - | - |
| 0.0108 | 11 | 4.828 | - | - | - |
| 0.0118 | 12 | 5.2269 | - | - | - |
| 0.0128 | 13 | 5.6772 | - | - | - |
| 0.0138 | 14 | 5.1422 | - | - | - |
| 0.0148 | 15 | 6.2469 | - | - | - |
| 0.0157 | 16 | 4.6802 | - | - | - |
| 0.0167 | 17 | 4.5492 | - | - | - |
| 0.0177 | 18 | 4.8062 | - | - | - |
| 0.0187 | 19 | 7.5141 | - | - | - |
| 0.0197 | 20 | 5.5202 | - | - | - |
| 0.0207 | 21 | 6.5025 | - | - | - |
| 0.0217 | 22 | 7.318 | - | - | - |
| 0.0226 | 23 | 4.6458 | - | - | - |
| 0.0236 | 24 | 4.6191 | - | - | - |
| 0.0246 | 25 | 4.3159 | - | - | - |
| 0.0256 | 26 | 6.3677 | - | - | - |
| 0.0266 | 27 | 5.6052 | - | - | - |
| 0.0276 | 28 | 4.196 | - | - | - |
| 0.0285 | 29 | 4.4802 | - | - | - |
| 0.0295 | 30 | 4.9193 | - | - | - |
| 0.0305 | 31 | 4.0996 | - | - | - |
| 0.0315 | 32 | 5.6307 | - | - | - |
| 0.0325 | 33 | 4.5745 | - | - | - |
| 0.0335 | 34 | 4.4514 | - | - | - |
| 0.0344 | 35 | 4.0617 | - | - | - |
| 0.0354 | 36 | 5.0298 | - | - | - |
| 0.0364 | 37 | 3.9815 | - | - | - |
| 0.0374 | 38 | 4.0871 | - | - | - |
| 0.0384 | 39 | 4.2378 | - | - | - |
| 0.0394 | 40 | 3.8226 | - | - | - |
| 0.0404 | 41 | 4.3519 | - | - | - |
| 0.0413 | 42 | 3.6345 | - | - | - |
| 0.0423 | 43 | 5.0829 | - | - | - |
| 0.0433 | 44 | 4.6701 | - | - | - |
| 0.0443 | 45 | 4.1371 | - | - | - |
| 0.0453 | 46 | 4.2418 | - | - | - |
| 0.0463 | 47 | 4.4766 | - | - | - |
| 0.0472 | 48 | 4.4797 | - | - | - |
| 0.0482 | 49 | 3.8471 | - | - | - |
| 0.0492 | 50 | 4.3194 | - | - | - |
| 0.0502 | 51 | 3.9426 | - | - | - |
| 0.0512 | 52 | 3.5333 | - | - | - |
| 0.0522 | 53 | 4.2426 | - | - | - |
| 0.0531 | 54 | 3.9816 | - | - | - |
| 0.0541 | 55 | 3.663 | - | - | - |
| 0.0551 | 56 | 3.9057 | - | - | - |
| 0.0561 | 57 | 4.0345 | - | - | - |
| 0.0571 | 58 | 3.5233 | - | - | - |
| 0.0581 | 59 | 3.7999 | - | - | - |
| 0.0591 | 60 | 3.1885 | - | - | - |
| 0.0600 | 61 | 3.6013 | - | - | - |
| 0.0610 | 62 | 3.392 | - | - | - |
| 0.0620 | 63 | 3.3814 | - | - | - |
| 0.0630 | 64 | 4.0428 | - | - | - |
| 0.0640 | 65 | 3.7825 | - | - | - |
| 0.0650 | 66 | 3.4181 | - | - | - |
| 0.0659 | 67 | 3.7793 | - | - | - |
| 0.0669 | 68 | 3.8344 | - | - | - |
| 0.0679 | 69 | 3.2165 | - | - | - |
| 0.0689 | 70 | 3.3811 | - | - | - |
| 0.0699 | 71 | 3.5984 | - | - | - |
| 0.0709 | 72 | 3.8583 | - | - | - |
| 0.0719 | 73 | 3.296 | - | - | - |
| 0.0728 | 74 | 2.7661 | - | - | - |
| 0.0738 | 75 | 2.9805 | - | - | - |
| 0.0748 | 76 | 2.566 | - | - | - |
| 0.0758 | 77 | 3.258 | - | - | - |
| 0.0768 | 78 | 3.3804 | - | - | - |
| 0.0778 | 79 | 2.8828 | - | - | - |
| 0.0787 | 80 | 3.1077 | - | - | - |
| 0.0797 | 81 | 2.9441 | - | - | - |
| 0.0807 | 82 | 2.9465 | - | - | - |
| 0.0817 | 83 | 2.7088 | - | - | - |
| 0.0827 | 84 | 2.9215 | - | - | - |
| 0.0837 | 85 | 3.4698 | - | - | - |
| 0.0846 | 86 | 2.2414 | - | - | - |
| 0.0856 | 87 | 3.1601 | - | - | - |
| 0.0866 | 88 | 2.7714 | - | - | - |
| 0.0876 | 89 | 3.0311 | - | - | - |
| 0.0886 | 90 | 3.0336 | - | - | - |
| 0.0896 | 91 | 1.9358 | - | - | - |
| 0.0906 | 92 | 2.6031 | - | - | - |
| 0.0915 | 93 | 2.7515 | - | - | - |
| 0.0925 | 94 | 2.8496 | - | - | - |
| 0.0935 | 95 | 1.8015 | - | - | - |
| 0.0945 | 96 | 2.8138 | - | - | - |
| 0.0955 | 97 | 2.0597 | - | - | - |
| 0.0965 | 98 | 2.1053 | - | - | - |
| 0.0974 | 99 | 2.6785 | - | - | - |
| 0.0984 | 100 | 2.588 | - | - | - |
| 0.0994 | 101 | 2.0099 | - | - | - |
| 0.1004 | 102 | 2.7947 | - | - | - |
| 0.1014 | 103 | 2.3274 | - | - | - |
| 0.1024 | 104 | 2.2545 | - | - | - |
| 0.1033 | 105 | 2.4575 | - | - | - |
| 0.1043 | 106 | 2.4413 | - | - | - |
| 0.1053 | 107 | 2.3185 | - | - | - |
| 0.1063 | 108 | 2.1577 | - | - | - |
| 0.1073 | 109 | 2.1278 | - | - | - |
| 0.1083 | 110 | 2.0967 | - | - | - |
| 0.1093 | 111 | 2.6142 | - | - | - |
| 0.1102 | 112 | 1.8553 | - | - | - |
| 0.1112 | 113 | 2.1523 | - | - | - |
| 0.1122 | 114 | 2.1726 | - | - | - |
| 0.1132 | 115 | 1.8564 | - | - | - |
| 0.1142 | 116 | 1.8413 | - | - | - |
| 0.1152 | 117 | 2.0441 | - | - | - |
| 0.1161 | 118 | 2.2159 | - | - | - |
| 0.1171 | 119 | 2.6779 | - | - | - |
| 0.1181 | 120 | 2.2976 | - | - | - |
| 0.1191 | 121 | 1.9407 | - | - | - |
| 0.1201 | 122 | 1.9019 | - | - | - |
| 0.1211 | 123 | 2.2149 | - | - | - |
| 0.1220 | 124 | 1.6823 | - | - | - |
| 0.1230 | 125 | 1.8402 | - | - | - |
| 0.1240 | 126 | 1.6914 | - | - | - |
| 0.125 | 127 | 2.1626 | - | - | - |
| 0.1260 | 128 | 1.6414 | - | - | - |
| 0.1270 | 129 | 2.2043 | - | - | - |
| 0.1280 | 130 | 1.9987 | - | - | - |
| 0.1289 | 131 | 1.8868 | - | - | - |
| 0.1299 | 132 | 1.8262 | - | - | - |
| 0.1309 | 133 | 2.0404 | - | - | - |
| 0.1319 | 134 | 1.9134 | - | - | - |
| 0.1329 | 135 | 2.3725 | - | - | - |
| 0.1339 | 136 | 1.4127 | - | - | - |
| 0.1348 | 137 | 1.6876 | - | - | - |
| 0.1358 | 138 | 1.8376 | - | - | - |
| 0.1368 | 139 | 1.6992 | - | - | - |
| 0.1378 | 140 | 1.5032 | - | - | - |
| 0.1388 | 141 | 2.0334 | - | - | - |
| 0.1398 | 142 | 2.3581 | - | - | - |
| 0.1407 | 143 | 1.4236 | - | - | - |
| 0.1417 | 144 | 2.202 | - | - | - |
| 0.1427 | 145 | 1.7654 | - | - | - |
| 0.1437 | 146 | 1.5748 | - | - | - |
| 0.1447 | 147 | 1.7996 | - | - | - |
| 0.1457 | 148 | 1.7517 | - | - | - |
| 0.1467 | 149 | 1.8933 | - | - | - |
| 0.1476 | 150 | 1.2836 | - | - | - |
| 0.1486 | 151 | 1.7145 | - | - | - |
| 0.1496 | 152 | 1.6499 | - | - | - |
| 0.1506 | 153 | 1.8273 | 0.4057 | 0.4389 | 0.6725 |
| 0.1516 | 154 | 2.2859 | - | - | - |
| 0.1526 | 155 | 1.0833 | - | - | - |
| 0.1535 | 156 | 1.6829 | - | - | - |
| 0.1545 | 157 | 2.1464 | - | - | - |
| 0.1555 | 158 | 1.745 | - | - | - |
| 0.1565 | 159 | 1.7319 | - | - | - |
| 0.1575 | 160 | 1.6968 | - | - | - |
| 0.1585 | 161 | 1.7401 | - | - | - |
| 0.1594 | 162 | 1.729 | - | - | - |
| 0.1604 | 163 | 2.0782 | - | - | - |
| 0.1614 | 164 | 2.6545 | - | - | - |
| 0.1624 | 165 | 1.4045 | - | - | - |
| 0.1634 | 166 | 1.2937 | - | - | - |
| 0.1644 | 167 | 1.1171 | - | - | - |
| 0.1654 | 168 | 1.3537 | - | - | - |
| 0.1663 | 169 | 1.7028 | - | - | - |
| 0.1673 | 170 | 1.4143 | - | - | - |
| 0.1683 | 171 | 1.8648 | - | - | - |
| 0.1693 | 172 | 1.6768 | - | - | - |
| 0.1703 | 173 | 1.9528 | - | - | - |
| 0.1713 | 174 | 1.1718 | - | - | - |
| 0.1722 | 175 | 1.8176 | - | - | - |
| 0.1732 | 176 | 0.8439 | - | - | - |
| 0.1742 | 177 | 1.5092 | - | - | - |
| 0.1752 | 178 | 1.1947 | - | - | - |
| 0.1762 | 179 | 1.6395 | - | - | - |
| 0.1772 | 180 | 1.4394 | - | - | - |
| 0.1781 | 181 | 1.7548 | - | - | - |
| 0.1791 | 182 | 1.1181 | - | - | - |
| 0.1801 | 183 | 1.0271 | - | - | - |
| 0.1811 | 184 | 2.3108 | - | - | - |
| 0.1821 | 185 | 2.1242 | - | - | - |
| 0.1831 | 186 | 1.9822 | - | - | - |
| 0.1841 | 187 | 2.3605 | - | - | - |
| 0.1850 | 188 | 1.5251 | - | - | - |
| 0.1860 | 189 | 1.2351 | - | - | - |
| 0.1870 | 190 | 1.5859 | - | - | - |
| 0.1880 | 191 | 1.8056 | - | - | - |
| 0.1890 | 192 | 1.349 | - | - | - |
| 0.1900 | 193 | 0.893 | - | - | - |
| 0.1909 | 194 | 1.5122 | - | - | - |
| 0.1919 | 195 | 1.3875 | - | - | - |
| 0.1929 | 196 | 1.29 | - | - | - |
| 0.1939 | 197 | 2.2931 | - | - | - |
| 0.1949 | 198 | 1.2663 | - | - | - |
| 0.1959 | 199 | 1.9712 | - | - | - |
| 0.1969 | 200 | 2.3307 | - | - | - |
| 0.1978 | 201 | 1.6544 | - | - | - |
| 0.1988 | 202 | 1.638 | - | - | - |
| 0.1998 | 203 | 1.3412 | - | - | - |
| 0.2008 | 204 | 1.4454 | - | - | - |
| 0.2018 | 205 | 1.5437 | - | - | - |
| 0.2028 | 206 | 1.4921 | - | - | - |
| 0.2037 | 207 | 1.4298 | - | - | - |
| 0.2047 | 208 | 1.6174 | - | - | - |
| 0.2057 | 209 | 1.4137 | - | - | - |
| 0.2067 | 210 | 1.5652 | - | - | - |
| 0.2077 | 211 | 1.1631 | - | - | - |
| 0.2087 | 212 | 1.2351 | - | - | - |
| 0.2096 | 213 | 1.7537 | - | - | - |
| 0.2106 | 214 | 1.3186 | - | - | - |
| 0.2116 | 215 | 1.2258 | - | - | - |
| 0.2126 | 216 | 0.7695 | - | - | - |
| 0.2136 | 217 | 1.2775 | - | - | - |
| 0.2146 | 218 | 1.6795 | - | - | - |
| 0.2156 | 219 | 1.2862 | - | - | - |
| 0.2165 | 220 | 1.1723 | - | - | - |
| 0.2175 | 221 | 1.3322 | - | - | - |
| 0.2185 | 222 | 1.7564 | - | - | - |
| 0.2195 | 223 | 1.1071 | - | - | - |
| 0.2205 | 224 | 1.2011 | - | - | - |
| 0.2215 | 225 | 1.2303 | - | - | - |
| 0.2224 | 226 | 1.212 | - | - | - |
| 0.2234 | 227 | 1.0117 | - | - | - |
| 0.2244 | 228 | 1.1907 | - | - | - |
| 0.2254 | 229 | 2.1293 | - | - | - |
| 0.2264 | 230 | 1.3063 | - | - | - |
| 0.2274 | 231 | 1.2841 | - | - | - |
| 0.2283 | 232 | 1.3778 | - | - | - |
| 0.2293 | 233 | 1.2242 | - | - | - |
| 0.2303 | 234 | 0.9227 | - | - | - |
| 0.2313 | 235 | 1.2221 | - | - | - |
| 0.2323 | 236 | 2.1041 | - | - | - |
| 0.2333 | 237 | 1.3341 | - | - | - |
| 0.2343 | 238 | 1.0876 | - | - | - |
| 0.2352 | 239 | 1.3328 | - | - | - |
| 0.2362 | 240 | 1.2958 | - | - | - |
| 0.2372 | 241 | 1.1522 | - | - | - |
| 0.2382 | 242 | 1.7942 | - | - | - |
| 0.2392 | 243 | 1.1325 | - | - | - |
| 0.2402 | 244 | 1.6466 | - | - | - |
| 0.2411 | 245 | 1.4608 | - | - | - |
| 0.2421 | 246 | 0.6375 | - | - | - |
| 0.2431 | 247 | 2.0177 | - | - | - |
| 0.2441 | 248 | 1.2069 | - | - | - |
| 0.2451 | 249 | 0.7639 | - | - | - |
| 0.2461 | 250 | 1.3465 | - | - | - |
| 0.2470 | 251 | 1.064 | - | - | - |
| 0.2480 | 252 | 1.3757 | - | - | - |
| 0.2490 | 253 | 1.612 | - | - | - |
| 0.25 | 254 | 0.7917 | - | - | - |
| 0.2510 | 255 | 1.5515 | - | - | - |
| 0.2520 | 256 | 0.799 | - | - | - |
| 0.2530 | 257 | 0.9882 | - | - | - |
| 0.2539 | 258 | 1.1814 | - | - | - |
| 0.2549 | 259 | 0.6394 | - | - | - |
| 0.2559 | 260 | 1.4756 | - | - | - |
| 0.2569 | 261 | 0.5338 | - | - | - |
| 0.2579 | 262 | 0.9779 | - | - | - |
| 0.2589 | 263 | 1.5307 | - | - | - |
| 0.2598 | 264 | 1.1213 | - | - | - |
| 0.2608 | 265 | 0.9482 | - | - | - |
| 0.2618 | 266 | 0.9599 | - | - | - |
| 0.2628 | 267 | 1.4455 | - | - | - |
| 0.2638 | 268 | 1.6496 | - | - | - |
| 0.2648 | 269 | 0.7402 | - | - | - |
| 0.2657 | 270 | 0.7835 | - | - | - |
| 0.2667 | 271 | 0.7821 | - | - | - |
| 0.2677 | 272 | 1.5422 | - | - | - |
| 0.2687 | 273 | 1.0995 | - | - | - |
| 0.2697 | 274 | 1.378 | - | - | - |
| 0.2707 | 275 | 1.3562 | - | - | - |
| 0.2717 | 276 | 0.7376 | - | - | - |
| 0.2726 | 277 | 1.1678 | - | - | - |
| 0.2736 | 278 | 1.2989 | - | - | - |
| 0.2746 | 279 | 1.9559 | - | - | - |
| 0.2756 | 280 | 1.1237 | - | - | - |
| 0.2766 | 281 | 0.952 | - | - | - |
| 0.2776 | 282 | 1.6629 | - | - | - |
| 0.2785 | 283 | 1.871 | - | - | - |
| 0.2795 | 284 | 1.5946 | - | - | - |
| 0.2805 | 285 | 1.4456 | - | - | - |
| 0.2815 | 286 | 1.4085 | - | - | - |
| 0.2825 | 287 | 1.1394 | - | - | - |
| 0.2835 | 288 | 1.0315 | - | - | - |
| 0.2844 | 289 | 1.488 | - | - | - |
| 0.2854 | 290 | 1.4006 | - | - | - |
| 0.2864 | 291 | 0.9237 | - | - | - |
| 0.2874 | 292 | 1.163 | - | - | - |
| 0.2884 | 293 | 1.7037 | - | - | - |
| 0.2894 | 294 | 0.8715 | - | - | - |
| 0.2904 | 295 | 1.2101 | - | - | - |
| 0.2913 | 296 | 1.1179 | - | - | - |
| 0.2923 | 297 | 1.3986 | - | - | - |
| 0.2933 | 298 | 1.7068 | - | - | - |
| 0.2943 | 299 | 0.8695 | - | - | - |
| 0.2953 | 300 | 1.3778 | - | - | - |
| 0.2963 | 301 | 1.2834 | - | - | - |
| 0.2972 | 302 | 0.8123 | - | - | - |
| 0.2982 | 303 | 1.6521 | - | - | - |
| 0.2992 | 304 | 1.1064 | - | - | - |
| 0.3002 | 305 | 0.9578 | - | - | - |
| 0.3012 | 306 | 0.9254 | 0.4888 | 0.4789 | 0.7040 |
| 0.3022 | 307 | 0.7541 | - | - | - |
| 0.3031 | 308 | 0.7324 | - | - | - |
| 0.3041 | 309 | 0.5974 | - | - | - |
| 0.3051 | 310 | 1.1481 | - | - | - |
| 0.3061 | 311 | 1.6179 | - | - | - |
| 0.3071 | 312 | 1.4641 | - | - | - |
| 0.3081 | 313 | 1.7185 | - | - | - |
| 0.3091 | 314 | 0.9328 | - | - | - |
| 0.3100 | 315 | 0.742 | - | - | - |
| 0.3110 | 316 | 1.4173 | - | - | - |
| 0.3120 | 317 | 0.7267 | - | - | - |
| 0.3130 | 318 | 0.9494 | - | - | - |
| 0.3140 | 319 | 1.5111 | - | - | - |
| 0.3150 | 320 | 1.6949 | - | - | - |
| 0.3159 | 321 | 1.7562 | - | - | - |
| 0.3169 | 322 | 1.2532 | - | - | - |
| 0.3179 | 323 | 1.1086 | - | - | - |
| 0.3189 | 324 | 0.7377 | - | - | - |
| 0.3199 | 325 | 1.085 | - | - | - |
| 0.3209 | 326 | 0.7767 | - | - | - |
| 0.3219 | 327 | 1.4441 | - | - | - |
| 0.3228 | 328 | 0.8146 | - | - | - |
| 0.3238 | 329 | 0.7403 | - | - | - |
| 0.3248 | 330 | 0.8476 | - | - | - |
| 0.3258 | 331 | 0.7323 | - | - | - |
| 0.3268 | 332 | 1.2241 | - | - | - |
| 0.3278 | 333 | 1.5065 | - | - | - |
| 0.3287 | 334 | 0.5259 | - | - | - |
| 0.3297 | 335 | 1.3103 | - | - | - |
| 0.3307 | 336 | 0.8655 | - | - | - |
| 0.3317 | 337 | 0.7575 | - | - | - |
| 0.3327 | 338 | 1.968 | - | - | - |
| 0.3337 | 339 | 1.317 | - | - | - |
| 0.3346 | 340 | 1.1972 | - | - | - |
| 0.3356 | 341 | 1.6323 | - | - | - |
| 0.3366 | 342 | 1.0469 | - | - | - |
| 0.3376 | 343 | 1.3349 | - | - | - |
| 0.3386 | 344 | 0.9544 | - | - | - |
| 0.3396 | 345 | 1.1894 | - | - | - |
| 0.3406 | 346 | 0.7717 | - | - | - |
| 0.3415 | 347 | 1.2563 | - | - | - |
| 0.3425 | 348 | 1.2437 | - | - | - |
| 0.3435 | 349 | 0.7806 | - | - | - |
| 0.3445 | 350 | 0.8303 | - | - | - |
| 0.3455 | 351 | 1.0926 | - | - | - |
| 0.3465 | 352 | 0.6654 | - | - | - |
| 0.3474 | 353 | 1.1087 | - | - | - |
| 0.3484 | 354 | 1.1525 | - | - | - |
| 0.3494 | 355 | 1.1127 | - | - | - |
| 0.3504 | 356 | 1.4267 | - | - | - |
| 0.3514 | 357 | 0.6148 | - | - | - |
| 0.3524 | 358 | 1.0123 | - | - | - |
| 0.3533 | 359 | 1.9682 | - | - | - |
| 0.3543 | 360 | 0.8487 | - | - | - |
| 0.3553 | 361 | 1.0412 | - | - | - |
| 0.3563 | 362 | 1.0902 | - | - | - |
| 0.3573 | 363 | 0.9606 | - | - | - |
| 0.3583 | 364 | 0.9206 | - | - | - |
| 0.3593 | 365 | 1.4727 | - | - | - |
| 0.3602 | 366 | 0.9379 | - | - | - |
| 0.3612 | 367 | 0.8387 | - | - | - |
| 0.3622 | 368 | 0.9692 | - | - | - |
| 0.3632 | 369 | 1.6298 | - | - | - |
| 0.3642 | 370 | 1.0882 | - | - | - |
| 0.3652 | 371 | 1.1558 | - | - | - |
| 0.3661 | 372 | 0.9546 | - | - | - |
| 0.3671 | 373 | 1.0124 | - | - | - |
| 0.3681 | 374 | 1.3916 | - | - | - |
| 0.3691 | 375 | 0.527 | - | - | - |
| 0.3701 | 376 | 0.6387 | - | - | - |
| 0.3711 | 377 | 1.1445 | - | - | - |
| 0.3720 | 378 | 1.3309 | - | - | - |
| 0.3730 | 379 | 1.5888 | - | - | - |
| 0.3740 | 380 | 1.4422 | - | - | - |
| 0.375 | 381 | 1.7044 | - | - | - |
| 0.3760 | 382 | 0.7913 | - | - | - |
| 0.3770 | 383 | 1.3241 | - | - | - |
| 0.3780 | 384 | 0.6473 | - | - | - |
| 0.3789 | 385 | 1.221 | - | - | - |
| 0.3799 | 386 | 0.7773 | - | - | - |
| 0.3809 | 387 | 1.054 | - | - | - |
| 0.3819 | 388 | 0.9862 | - | - | - |
| 0.3829 | 389 | 0.9684 | - | - | - |
| 0.3839 | 390 | 1.3244 | - | - | - |
| 0.3848 | 391 | 1.1787 | - | - | - |
| 0.3858 | 392 | 1.4698 | - | - | - |
| 0.3868 | 393 | 1.0961 | - | - | - |
| 0.3878 | 394 | 1.1364 | - | - | - |
| 0.3888 | 395 | 0.9368 | - | - | - |
| 0.3898 | 396 | 1.1731 | - | - | - |
| 0.3907 | 397 | 0.8686 | - | - | - |
| 0.3917 | 398 | 0.7481 | - | - | - |
| 0.3927 | 399 | 0.7261 | - | - | - |
| 0.3937 | 400 | 1.2062 | - | - | - |
| 0.3947 | 401 | 0.7462 | - | - | - |
| 0.3957 | 402 | 1.0318 | - | - | - |
| 0.3967 | 403 | 1.105 | - | - | - |
| 0.3976 | 404 | 1.009 | - | - | - |
| 0.3986 | 405 | 0.5941 | - | - | - |
| 0.3996 | 406 | 1.7972 | - | - | - |
| 0.4006 | 407 | 1.0544 | - | - | - |
| 0.4016 | 408 | 1.3912 | - | - | - |
| 0.4026 | 409 | 0.8305 | - | - | - |
| 0.4035 | 410 | 0.8688 | - | - | - |
| 0.4045 | 411 | 1.0069 | - | - | - |
| 0.4055 | 412 | 1.3141 | - | - | - |
| 0.4065 | 413 | 1.1042 | - | - | - |
| 0.4075 | 414 | 1.1011 | - | - | - |
| 0.4085 | 415 | 1.1192 | - | - | - |
| 0.4094 | 416 | 1.5957 | - | - | - |
| 0.4104 | 417 | 1.164 | - | - | - |
| 0.4114 | 418 | 0.6425 | - | - | - |
| 0.4124 | 419 | 0.6068 | - | - | - |
| 0.4134 | 420 | 0.9275 | - | - | - |
| 0.4144 | 421 | 0.8836 | - | - | - |
| 0.4154 | 422 | 1.2115 | - | - | - |
| 0.4163 | 423 | 0.8367 | - | - | - |
| 0.4173 | 424 | 1.0595 | - | - | - |
| 0.4183 | 425 | 0.826 | - | - | - |
| 0.4193 | 426 | 0.707 | - | - | - |
| 0.4203 | 427 | 0.6235 | - | - | - |
| 0.4213 | 428 | 0.7719 | - | - | - |
| 0.4222 | 429 | 1.0862 | - | - | - |
| 0.4232 | 430 | 0.9311 | - | - | - |
| 0.4242 | 431 | 1.2339 | - | - | - |
| 0.4252 | 432 | 0.9891 | - | - | - |
| 0.4262 | 433 | 1.8443 | - | - | - |
| 0.4272 | 434 | 1.1799 | - | - | - |
| 0.4281 | 435 | 0.759 | - | - | - |
| 0.4291 | 436 | 1.1002 | - | - | - |
| 0.4301 | 437 | 0.9141 | - | - | - |
| 0.4311 | 438 | 0.5467 | - | - | - |
| 0.4321 | 439 | 0.7476 | - | - | - |
| 0.4331 | 440 | 1.14 | - | - | - |
| 0.4341 | 441 | 1.1504 | - | - | - |
| 0.4350 | 442 | 1.26 | - | - | - |
| 0.4360 | 443 | 1.0311 | - | - | - |
| 0.4370 | 444 | 1.0646 | - | - | - |
| 0.4380 | 445 | 0.8687 | - | - | - |
| 0.4390 | 446 | 0.6839 | - | - | - |
| 0.4400 | 447 | 1.1376 | - | - | - |
| 0.4409 | 448 | 0.9759 | - | - | - |
| 0.4419 | 449 | 0.7971 | - | - | - |
| 0.4429 | 450 | 0.9708 | - | - | - |
| 0.4439 | 451 | 0.8217 | - | - | - |
| 0.4449 | 452 | 1.3728 | - | - | - |
| 0.4459 | 453 | 0.9119 | - | - | - |
| 0.4469 | 454 | 1.012 | - | - | - |
| 0.4478 | 455 | 1.3738 | - | - | - |
| 0.4488 | 456 | 0.8219 | - | - | - |
| 0.4498 | 457 | 1.2558 | - | - | - |
| 0.4508 | 458 | 0.6247 | - | - | - |
| 0.4518 | 459 | 0.7295 | 0.5410 | 0.4920 | 0.6879 |
| 0.4528 | 460 | 0.8154 | - | - | - |
| 0.4537 | 461 | 1.1392 | - | - | - |
| 0.4547 | 462 | 0.8618 | - | - | - |
| 0.4557 | 463 | 0.9669 | - | - | - |
| 0.4567 | 464 | 0.8804 | - | - | - |
| 0.4577 | 465 | 0.8479 | - | - | - |
| 0.4587 | 466 | 0.6296 | - | - | - |
| 0.4596 | 467 | 0.8449 | - | - | - |
| 0.4606 | 468 | 0.9772 | - | - | - |
| 0.4616 | 469 | 0.6424 | - | - | - |
| 0.4626 | 470 | 0.9169 | - | - | - |
| 0.4636 | 471 | 0.7599 | - | - | - |
| 0.4646 | 472 | 0.8943 | - | - | - |
| 0.4656 | 473 | 0.9475 | - | - | - |
| 0.4665 | 474 | 1.4518 | - | - | - |
| 0.4675 | 475 | 1.274 | - | - | - |
| 0.4685 | 476 | 0.7306 | - | - | - |
| 0.4695 | 477 | 0.9238 | - | - | - |
| 0.4705 | 478 | 0.6593 | - | - | - |
| 0.4715 | 479 | 1.0183 | - | - | - |
| 0.4724 | 480 | 1.2577 | - | - | - |
| 0.4734 | 481 | 0.8738 | - | - | - |
| 0.4744 | 482 | 1.1416 | - | - | - |
| 0.4754 | 483 | 0.7135 | - | - | - |
| 0.4764 | 484 | 1.2587 | - | - | - |
| 0.4774 | 485 | 0.8823 | - | - | - |
| 0.4783 | 486 | 0.8423 | - | - | - |
| 0.4793 | 487 | 0.7704 | - | - | - |
| 0.4803 | 488 | 0.7049 | - | - | - |
| 0.4813 | 489 | 1.1893 | - | - | - |
| 0.4823 | 490 | 1.3985 | - | - | - |
| 0.4833 | 491 | 1.3567 | - | - | - |
| 0.4843 | 492 | 1.2573 | - | - | - |
| 0.4852 | 493 | 0.7671 | - | - | - |
| 0.4862 | 494 | 0.5425 | - | - | - |
| 0.4872 | 495 | 0.9372 | - | - | - |
| 0.4882 | 496 | 0.799 | - | - | - |
| 0.4892 | 497 | 0.9548 | - | - | - |
| 0.4902 | 498 | 1.0855 | - | - | - |
| 0.4911 | 499 | 1.0465 | - | - | - |
| 0.4921 | 500 | 1.1004 | - | - | - |
| 0.4931 | 501 | 0.6392 | - | - | - |
| 0.4941 | 502 | 0.7102 | - | - | - |
| 0.4951 | 503 | 1.3242 | - | - | - |
| 0.4961 | 504 | 0.6861 | - | - | - |
| 0.4970 | 505 | 0.9291 | - | - | - |
| 0.4980 | 506 | 0.8592 | - | - | - |
| 0.4990 | 507 | 0.9462 | - | - | - |
| 0.5 | 508 | 1.0167 | - | - | - |
| 0.5010 | 509 | 1.0118 | - | - | - |
| 0.5020 | 510 | 0.6741 | - | - | - |
| 0.5030 | 511 | 1.4578 | - | - | - |
| 0.5039 | 512 | 1.2959 | - | - | - |
| 0.5049 | 513 | 0.8533 | - | - | - |
| 0.5059 | 514 | 0.6685 | - | - | - |
| 0.5069 | 515 | 1.1556 | - | - | - |
| 0.5079 | 516 | 0.8177 | - | - | - |
| 0.5089 | 517 | 0.6296 | - | - | - |
| 0.5098 | 518 | 0.8407 | - | - | - |
| 0.5108 | 519 | 0.6987 | - | - | - |
| 0.5118 | 520 | 0.9888 | - | - | - |
| 0.5128 | 521 | 0.8938 | - | - | - |
| 0.5138 | 522 | 0.582 | - | - | - |
| 0.5148 | 523 | 0.6596 | - | - | - |
| 0.5157 | 524 | 0.6029 | - | - | - |
| 0.5167 | 525 | 0.9806 | - | - | - |
| 0.5177 | 526 | 0.9463 | - | - | - |
| 0.5187 | 527 | 0.7088 | - | - | - |
| 0.5197 | 528 | 0.7525 | - | - | - |
| 0.5207 | 529 | 0.7625 | - | - | - |
| 0.5217 | 530 | 0.8271 | - | - | - |
| 0.5226 | 531 | 0.6129 | - | - | - |
| 0.5236 | 532 | 1.1563 | - | - | - |
| 0.5246 | 533 | 0.8131 | - | - | - |
| 0.5256 | 534 | 0.5363 | - | - | - |
| 0.5266 | 535 | 0.8819 | - | - | - |
| 0.5276 | 536 | 0.9772 | - | - | - |
| 0.5285 | 537 | 1.2102 | - | - | - |
| 0.5295 | 538 | 1.1234 | - | - | - |
| 0.5305 | 539 | 1.1857 | - | - | - |
| 0.5315 | 540 | 0.7873 | - | - | - |
| 0.5325 | 541 | 0.5034 | - | - | - |
| 0.5335 | 542 | 1.3305 | - | - | - |
| 0.5344 | 543 | 1.1727 | - | - | - |
| 0.5354 | 544 | 1.2825 | - | - | - |
| 0.5364 | 545 | 1.0446 | - | - | - |
| 0.5374 | 546 | 0.9838 | - | - | - |
| 0.5384 | 547 | 1.2194 | - | - | - |
| 0.5394 | 548 | 0.7709 | - | - | - |
| 0.5404 | 549 | 0.748 | - | - | - |
| 0.5413 | 550 | 1.0948 | - | - | - |
| 0.5423 | 551 | 0.915 | - | - | - |
| 0.5433 | 552 | 1.537 | - | - | - |
| 0.5443 | 553 | 0.3239 | - | - | - |
| 0.5453 | 554 | 0.9592 | - | - | - |
| 0.5463 | 555 | 0.7737 | - | - | - |
| 0.5472 | 556 | 0.613 | - | - | - |
| 0.5482 | 557 | 1.3646 | - | - | - |
| 0.5492 | 558 | 0.6659 | - | - | - |
| 0.5502 | 559 | 0.5207 | - | - | - |
| 0.5512 | 560 | 0.9467 | - | - | - |
| 0.5522 | 561 | 0.5692 | - | - | - |
| 0.5531 | 562 | 1.5855 | - | - | - |
| 0.5541 | 563 | 0.8855 | - | - | - |
| 0.5551 | 564 | 1.1829 | - | - | - |
| 0.5561 | 565 | 0.978 | - | - | - |
| 0.5571 | 566 | 1.1818 | - | - | - |
| 0.5581 | 567 | 0.701 | - | - | - |
| 0.5591 | 568 | 1.0226 | - | - | - |
| 0.5600 | 569 | 0.5937 | - | - | - |
| 0.5610 | 570 | 0.8095 | - | - | - |
| 0.5620 | 571 | 1.174 | - | - | - |
| 0.5630 | 572 | 0.96 | - | - | - |
| 0.5640 | 573 | 0.8339 | - | - | - |
| 0.5650 | 574 | 0.717 | - | - | - |
| 0.5659 | 575 | 0.5938 | - | - | - |
| 0.5669 | 576 | 0.6501 | - | - | - |
| 0.5679 | 577 | 0.7003 | - | - | - |
| 0.5689 | 578 | 0.5525 | - | - | - |
| 0.5699 | 579 | 0.7003 | - | - | - |
| 0.5709 | 580 | 1.059 | - | - | - |
| 0.5719 | 581 | 0.8625 | - | - | - |
| 0.5728 | 582 | 0.5862 | - | - | - |
| 0.5738 | 583 | 0.9162 | - | - | - |
| 0.5748 | 584 | 0.926 | - | - | - |
| 0.5758 | 585 | 1.2729 | - | - | - |
| 0.5768 | 586 | 0.8935 | - | - | - |
| 0.5778 | 587 | 0.541 | - | - | - |
| 0.5787 | 588 | 1.1455 | - | - | - |
| 0.5797 | 589 | 0.7306 | - | - | - |
| 0.5807 | 590 | 0.9088 | - | - | - |
| 0.5817 | 591 | 0.9166 | - | - | - |
| 0.5827 | 592 | 0.8679 | - | - | - |
| 0.5837 | 593 | 0.9329 | - | - | - |
| 0.5846 | 594 | 1.1201 | - | - | - |
| 0.5856 | 595 | 0.6418 | - | - | - |
| 0.5866 | 596 | 1.145 | - | - | - |
| 0.5876 | 597 | 1.4041 | - | - | - |
| 0.5886 | 598 | 0.6954 | - | - | - |
| 0.5896 | 599 | 0.4567 | - | - | - |
| 0.5906 | 600 | 1.1305 | - | - | - |
| 0.5915 | 601 | 0.8077 | - | - | - |
| 0.5925 | 602 | 0.6143 | - | - | - |
| 0.5935 | 603 | 1.3139 | - | - | - |
| 0.5945 | 604 | 0.7694 | - | - | - |
| 0.5955 | 605 | 0.9622 | - | - | - |
| 0.5965 | 606 | 0.91 | - | - | - |
| 0.5974 | 607 | 1.3125 | - | - | - |
| 0.5984 | 608 | 1.0153 | - | - | - |
| 0.5994 | 609 | 0.8468 | - | - | - |
| 0.6004 | 610 | 1.1026 | - | - | - |
| 0.6014 | 611 | 0.8291 | - | - | - |
| 0.6024 | 612 | 0.7235 | 0.5680 | 0.5175 | 0.6900 |
| 0.6033 | 613 | 0.9613 | - | - | - |
| 0.6043 | 614 | 0.7124 | - | - | - |
| 0.6053 | 615 | 1.0719 | - | - | - |
| 0.6063 | 616 | 0.7233 | - | - | - |
| 0.6073 | 617 | 1.6863 | - | - | - |
| 0.6083 | 618 | 0.8665 | - | - | - |
| 0.6093 | 619 | 1.6432 | - | - | - |
| 0.6102 | 620 | 0.771 | - | - | - |
| 0.6112 | 621 | 0.6755 | - | - | - |
| 0.6122 | 622 | 0.6809 | - | - | - |
| 0.6132 | 623 | 0.5626 | - | - | - |
| 0.6142 | 624 | 0.6287 | - | - | - |
| 0.6152 | 625 | 0.5478 | - | - | - |
| 0.6161 | 626 | 0.9155 | - | - | - |
| 0.6171 | 627 | 1.8947 | - | - | - |
| 0.6181 | 628 | 1.1943 | - | - | - |
| 0.6191 | 629 | 1.2465 | - | - | - |
| 0.6201 | 630 | 0.4045 | - | - | - |
| 0.6211 | 631 | 0.5688 | - | - | - |
| 0.6220 | 632 | 0.8682 | - | - | - |
| 0.6230 | 633 | 0.901 | - | - | - |
| 0.6240 | 634 | 0.8978 | - | - | - |
| 0.625 | 635 | 0.6592 | - | - | - |
| 0.6260 | 636 | 0.6828 | - | - | - |
| 0.6270 | 637 | 0.3995 | - | - | - |
| 0.6280 | 638 | 0.8283 | - | - | - |
| 0.6289 | 639 | 0.5938 | - | - | - |
| 0.6299 | 640 | 1.256 | - | - | - |
| 0.6309 | 641 | 0.7801 | - | - | - |
| 0.6319 | 642 | 0.8975 | - | - | - |
| 0.6329 | 643 | 1.255 | - | - | - |
| 0.6339 | 644 | 1.1252 | - | - | - |
| 0.6348 | 645 | 1.2394 | - | - | - |
| 0.6358 | 646 | 0.9579 | - | - | - |
| 0.6368 | 647 | 0.8664 | - | - | - |
| 0.6378 | 648 | 0.4087 | - | - | - |
| 0.6388 | 649 | 0.4084 | - | - | - |
| 0.6398 | 650 | 0.6214 | - | - | - |
| 0.6407 | 651 | 0.7237 | - | - | - |
| 0.6417 | 652 | 0.6294 | - | - | - |
| 0.6427 | 653 | 0.8264 | - | - | - |
| 0.6437 | 654 | 0.8258 | - | - | - |
| 0.6447 | 655 | 0.6865 | - | - | - |
| 0.6457 | 656 | 0.7408 | - | - | - |
| 0.6467 | 657 | 0.6196 | - | - | - |
| 0.6476 | 658 | 0.5659 | - | - | - |
| 0.6486 | 659 | 0.6353 | - | - | - |
| 0.6496 | 660 | 0.8432 | - | - | - |
| 0.6506 | 661 | 0.6573 | - | - | - |
| 0.6516 | 662 | 0.4918 | - | - | - |
| 0.6526 | 663 | 0.8571 | - | - | - |
| 0.6535 | 664 | 0.9105 | - | - | - |
| 0.6545 | 665 | 0.7499 | - | - | - |
| 0.6555 | 666 | 0.5277 | - | - | - |
| 0.6565 | 667 | 1.3046 | - | - | - |
| 0.6575 | 668 | 0.6112 | - | - | - |
| 0.6585 | 669 | 0.754 | - | - | - |
| 0.6594 | 670 | 1.3611 | - | - | - |
| 0.6604 | 671 | 1.3654 | - | - | - |
| 0.6614 | 672 | 0.6479 | - | - | - |
| 0.6624 | 673 | 0.9422 | - | - | - |
| 0.6634 | 674 | 0.5007 | - | - | - |
| 0.6644 | 675 | 0.4789 | - | - | - |
| 0.6654 | 676 | 0.3962 | - | - | - |
| 0.6663 | 677 | 0.8648 | - | - | - |
| 0.6673 | 678 | 0.8241 | - | - | - |
| 0.6683 | 679 | 0.7923 | - | - | - |
| 0.6693 | 680 | 0.5799 | - | - | - |
| 0.6703 | 681 | 0.8422 | - | - | - |
| 0.6713 | 682 | 0.5638 | - | - | - |
| 0.6722 | 683 | 0.9627 | - | - | - |
| 0.6732 | 684 | 0.7585 | - | - | - |
| 0.6742 | 685 | 0.488 | - | - | - |
| 0.6752 | 686 | 1.0991 | - | - | - |
| 0.6762 | 687 | 0.4808 | - | - | - |
| 0.6772 | 688 | 1.3717 | - | - | - |
| 0.6781 | 689 | 0.8225 | - | - | - |
| 0.6791 | 690 | 0.9377 | - | - | - |
| 0.6801 | 691 | 0.8016 | - | - | - |
| 0.6811 | 692 | 0.6257 | - | - | - |
| 0.6821 | 693 | 1.0941 | - | - | - |
| 0.6831 | 694 | 1.0878 | - | - | - |
| 0.6841 | 695 | 0.9231 | - | - | - |
| 0.6850 | 696 | 1.3284 | - | - | - |
| 0.6860 | 697 | 0.7274 | - | - | - |
| 0.6870 | 698 | 0.7851 | - | - | - |
| 0.6880 | 699 | 0.6807 | - | - | - |
| 0.6890 | 700 | 1.1592 | - | - | - |
| 0.6900 | 701 | 0.6347 | - | - | - |
| 0.6909 | 702 | 1.1326 | - | - | - |
| 0.6919 | 703 | 1.3797 | - | - | - |
| 0.6929 | 704 | 0.7782 | - | - | - |
| 0.6939 | 705 | 1.1746 | - | - | - |
| 0.6949 | 706 | 0.7624 | - | - | - |
| 0.6959 | 707 | 0.7216 | - | - | - |
| 0.6969 | 708 | 0.4666 | - | - | - |
| 0.6978 | 709 | 0.9398 | - | - | - |
| 0.6988 | 710 | 0.9532 | - | - | - |
| 0.6998 | 711 | 0.8285 | - | - | - |
| 0.7008 | 712 | 0.7042 | - | - | - |
| 0.7018 | 713 | 1.0057 | - | - | - |
| 0.7028 | 714 | 0.6696 | - | - | - |
| 0.7037 | 715 | 0.5701 | - | - | - |
| 0.7047 | 716 | 0.7894 | - | - | - |
| 0.7057 | 717 | 0.9327 | - | - | - |
| 0.7067 | 718 | 1.0283 | - | - | - |
| 0.7077 | 719 | 0.6419 | - | - | - |
| 0.7087 | 720 | 0.7716 | - | - | - |
| 0.7096 | 721 | 0.5968 | - | - | - |
| 0.7106 | 722 | 0.6547 | - | - | - |
| 0.7116 | 723 | 0.8344 | - | - | - |
| 0.7126 | 724 | 0.5448 | - | - | - |
| 0.7136 | 725 | 0.6075 | - | - | - |
| 0.7146 | 726 | 0.6142 | - | - | - |
| 0.7156 | 727 | 0.681 | - | - | - |
| 0.7165 | 728 | 0.6137 | - | - | - |
| 0.7175 | 729 | 1.4516 | - | - | - |
| 0.7185 | 730 | 0.9083 | - | - | - |
| 0.7195 | 731 | 0.6369 | - | - | - |
| 0.7205 | 732 | 0.8102 | - | - | - |
| 0.7215 | 733 | 0.7808 | - | - | - |
| 0.7224 | 734 | 0.512 | - | - | - |
| 0.7234 | 735 | 1.3589 | - | - | - |
| 0.7244 | 736 | 0.6555 | - | - | - |
| 0.7254 | 737 | 0.8732 | - | - | - |
| 0.7264 | 738 | 0.7591 | - | - | - |
| 0.7274 | 739 | 0.8237 | - | - | - |
| 0.7283 | 740 | 1.1272 | - | - | - |
| 0.7293 | 741 | 0.5353 | - | - | - |
| 0.7303 | 742 | 1.1713 | - | - | - |
| 0.7313 | 743 | 0.7034 | - | - | - |
| 0.7323 | 744 | 0.5118 | - | - | - |
| 0.7333 | 745 | 0.7816 | - | - | - |
| 0.7343 | 746 | 0.7935 | - | - | - |
| 0.7352 | 747 | 1.0736 | - | - | - |
| 0.7362 | 748 | 0.6528 | - | - | - |
| 0.7372 | 749 | 0.5556 | - | - | - |
| 0.7382 | 750 | 0.3339 | - | - | - |
| 0.7392 | 751 | 1.0371 | - | - | - |
| 0.7402 | 752 | 1.3273 | - | - | - |
| 0.7411 | 753 | 0.5307 | - | - | - |
| 0.7421 | 754 | 0.908 | - | - | - |
| 0.7431 | 755 | 0.5248 | - | - | - |
| 0.7441 | 756 | 0.6128 | - | - | - |
| 0.7451 | 757 | 1.5065 | - | - | - |
| 0.7461 | 758 | 1.2071 | - | - | - |
| 0.7470 | 759 | 0.9983 | - | - | - |
| 0.7480 | 760 | 1.0378 | - | - | - |
| 0.7490 | 761 | 1.0732 | - | - | - |
| 0.75 | 762 | 0.8046 | - | - | - |
| 0.7510 | 763 | 1.1666 | - | - | - |
| 0.7520 | 764 | 0.7042 | - | - | - |
| 0.7530 | 765 | 1.4759 | 0.5730 | 0.5105 | 0.6982 |
| 0.7539 | 766 | 0.5595 | - | - | - |
| 0.7549 | 767 | 0.3646 | - | - | - |
| 0.7559 | 768 | 0.6791 | - | - | - |
| 0.7569 | 769 | 0.6889 | - | - | - |
| 0.7579 | 770 | 0.9715 | - | - | - |
| 0.7589 | 771 | 1.2218 | - | - | - |
| 0.7598 | 772 | 0.3957 | - | - | - |
| 0.7608 | 773 | 1.5635 | - | - | - |
| 0.7618 | 774 | 0.9081 | - | - | - |
| 0.7628 | 775 | 0.8633 | - | - | - |
| 0.7638 | 776 | 0.9482 | - | - | - |
| 0.7648 | 777 | 0.8021 | - | - | - |
| 0.7657 | 778 | 0.9083 | - | - | - |
| 0.7667 | 779 | 0.9599 | - | - | - |
| 0.7677 | 780 | 0.798 | - | - | - |
| 0.7687 | 781 | 0.5817 | - | - | - |
| 0.7697 | 782 | 0.5287 | - | - | - |
| 0.7707 | 783 | 1.0251 | - | - | - |
| 0.7717 | 784 | 0.3995 | - | - | - |
| 0.7726 | 785 | 0.8753 | - | - | - |
| 0.7736 | 786 | 1.315 | - | - | - |
| 0.7746 | 787 | 0.8053 | - | - | - |
| 0.7756 | 788 | 0.6032 | - | - | - |
| 0.7766 | 789 | 0.8059 | - | - | - |
| 0.7776 | 790 | 0.9387 | - | - | - |
| 0.7785 | 791 | 0.8321 | - | - | - |
| 0.7795 | 792 | 0.5788 | - | - | - |
| 0.7805 | 793 | 0.7874 | - | - | - |
| 0.7815 | 794 | 0.5145 | - | - | - |
| 0.7825 | 795 | 1.5847 | - | - | - |
| 0.7835 | 796 | 1.1473 | - | - | - |
| 0.7844 | 797 | 0.968 | - | - | - |
| 0.7854 | 798 | 1.2691 | - | - | - |
| 0.7864 | 799 | 0.7046 | - | - | - |
| 0.7874 | 800 | 0.9358 | - | - | - |
| 0.7884 | 801 | 0.3945 | - | - | - |
| 0.7894 | 802 | 0.861 | - | - | - |
| 0.7904 | 803 | 1.0736 | - | - | - |
| 0.7913 | 804 | 1.0279 | - | - | - |
| 0.7923 | 805 | 0.6902 | - | - | - |
| 0.7933 | 806 | 0.7344 | - | - | - |
| 0.7943 | 807 | 0.8184 | - | - | - |
| 0.7953 | 808 | 0.8121 | - | - | - |
| 0.7963 | 809 | 0.3772 | - | - | - |
| 0.7972 | 810 | 0.2367 | - | - | - |
| 0.7982 | 811 | 0.5584 | - | - | - |
| 0.7992 | 812 | 0.3465 | - | - | - |
| 0.8002 | 813 | 0.9229 | - | - | - |
| 0.8012 | 814 | 0.7351 | - | - | - |
| 0.8022 | 815 | 0.9024 | - | - | - |
| 0.8031 | 816 | 0.4958 | - | - | - |
| 0.8041 | 817 | 0.4321 | - | - | - |
| 0.8051 | 818 | 0.6945 | - | - | - |
| 0.8061 | 819 | 0.6415 | - | - | - |
| 0.8071 | 820 | 0.5615 | - | - | - |
| 0.8081 | 821 | 0.9732 | - | - | - |
| 0.8091 | 822 | 1.018 | - | - | - |
| 0.8100 | 823 | 1.1392 | - | - | - |
| 0.8110 | 824 | 0.8539 | - | - | - |
| 0.8120 | 825 | 0.7081 | - | - | - |
| 0.8130 | 826 | 1.3176 | - | - | - |
| 0.8140 | 827 | 0.7387 | - | - | - |
| 0.8150 | 828 | 1.0975 | - | - | - |
| 0.8159 | 829 | 0.5883 | - | - | - |
| 0.8169 | 830 | 0.9677 | - | - | - |
| 0.8179 | 831 | 0.3869 | - | - | - |
| 0.8189 | 832 | 0.9083 | - | - | - |
| 0.8199 | 833 | 0.6939 | - | - | - |
| 0.8209 | 834 | 0.5046 | - | - | - |
| 0.8219 | 835 | 0.3594 | - | - | - |
| 0.8228 | 836 | 0.4609 | - | - | - |
| 0.8238 | 837 | 0.8132 | - | - | - |
| 0.8248 | 838 | 0.4493 | - | - | - |
| 0.8258 | 839 | 0.8566 | - | - | - |
| 0.8268 | 840 | 0.9958 | - | - | - |
| 0.8278 | 841 | 0.936 | - | - | - |
| 0.8287 | 842 | 1.4087 | - | - | - |
| 0.8297 | 843 | 1.2214 | - | - | - |
| 0.8307 | 844 | 0.7135 | - | - | - |
| 0.8317 | 845 | 1.1881 | - | - | - |
| 0.8327 | 846 | 1.1807 | - | - | - |
| 0.8337 | 847 | 0.5896 | - | - | - |
| 0.8346 | 848 | 0.8483 | - | - | - |
| 0.8356 | 849 | 0.5409 | - | - | - |
| 0.8366 | 850 | 0.8286 | - | - | - |
| 0.8376 | 851 | 1.136 | - | - | - |
| 0.8386 | 852 | 0.819 | - | - | - |
| 0.8396 | 853 | 0.3029 | - | - | - |
| 0.8406 | 854 | 0.5538 | - | - | - |
| 0.8415 | 855 | 0.4572 | - | - | - |
| 0.8425 | 856 | 1.1516 | - | - | - |
| 0.8435 | 857 | 0.4768 | - | - | - |
| 0.8445 | 858 | 0.5357 | - | - | - |
| 0.8455 | 859 | 0.8879 | - | - | - |
| 0.8465 | 860 | 0.9121 | - | - | - |
| 0.8474 | 861 | 1.052 | - | - | - |
| 0.8484 | 862 | 0.8009 | - | - | - |
| 0.8494 | 863 | 0.2474 | - | - | - |
| 0.8504 | 864 | 0.8517 | - | - | - |
| 0.8514 | 865 | 0.5678 | - | - | - |
| 0.8524 | 866 | 0.4882 | - | - | - |
| 0.8533 | 867 | 0.638 | - | - | - |
| 0.8543 | 868 | 0.8012 | - | - | - |
| 0.8553 | 869 | 0.4172 | - | - | - |
| 0.8563 | 870 | 0.6727 | - | - | - |
| 0.8573 | 871 | 0.6383 | - | - | - |
| 0.8583 | 872 | 1.0728 | - | - | - |
| 0.8593 | 873 | 1.3336 | - | - | - |
| 0.8602 | 874 | 1.217 | - | - | - |
| 0.8612 | 875 | 0.8018 | - | - | - |
| 0.8622 | 876 | 1.2326 | - | - | - |
| 0.8632 | 877 | 1.0898 | - | - | - |
| 0.8642 | 878 | 0.7192 | - | - | - |
| 0.8652 | 879 | 0.7779 | - | - | - |
| 0.8661 | 880 | 0.9291 | - | - | - |
| 0.8671 | 881 | 0.6333 | - | - | - |
| 0.8681 | 882 | 0.9028 | - | - | - |
| 0.8691 | 883 | 0.9904 | - | - | - |
| 0.8701 | 884 | 0.5775 | - | - | - |
| 0.8711 | 885 | 0.9783 | - | - | - |
| 0.8720 | 886 | 1.111 | - | - | - |
| 0.8730 | 887 | 1.0398 | - | - | - |
| 0.8740 | 888 | 0.742 | - | - | - |
| 0.875 | 889 | 0.7606 | - | - | - |
| 0.8760 | 890 | 0.6941 | - | - | - |
| 0.8770 | 891 | 1.0219 | - | - | - |
| 0.8780 | 892 | 0.8949 | - | - | - |
| 0.8789 | 893 | 1.0013 | - | - | - |
| 0.8799 | 894 | 1.1122 | - | - | - |
| 0.8809 | 895 | 1.1711 | - | - | - |
| 0.8819 | 896 | 0.7457 | - | - | - |
| 0.8829 | 897 | 0.5431 | - | - | - |
| 0.8839 | 898 | 0.8159 | - | - | - |
| 0.8848 | 899 | 1.6812 | - | - | - |
| 0.8858 | 900 | 0.8163 | - | - | - |
| 0.8868 | 901 | 0.9315 | - | - | - |
| 0.8878 | 902 | 0.883 | - | - | - |
| 0.8888 | 903 | 0.8014 | - | - | - |
| 0.8898 | 904 | 1.4277 | - | - | - |
| 0.8907 | 905 | 0.7507 | - | - | - |
| 0.8917 | 906 | 0.9757 | - | - | - |
| 0.8927 | 907 | 0.6366 | - | - | - |
| 0.8937 | 908 | 0.7567 | - | - | - |
| 0.8947 | 909 | 0.7853 | - | - | - |
| 0.8957 | 910 | 0.7611 | - | - | - |
| 0.8967 | 911 | 0.8417 | - | - | - |
| 0.8976 | 912 | 0.5825 | - | - | - |
| 0.8986 | 913 | 1.0816 | - | - | - |
| 0.8996 | 914 | 1.1768 | - | - | - |
| 0.9006 | 915 | 0.4894 | - | - | - |
| 0.9016 | 916 | 0.8739 | - | - | - |
| 0.9026 | 917 | 1.0047 | - | - | - |
| 0.9035 | 918 | 0.7733 | 0.6115 | 0.5123 | 0.7069 |
| 0.9045 | 919 | 1.1274 | - | - | - |
| 0.9055 | 920 | 1.5414 | - | - | - |
| 0.9065 | 921 | 1.0839 | - | - | - |
| 0.9075 | 922 | 0.5004 | - | - | - |
| 0.9085 | 923 | 0.8282 | - | - | - |
| 0.9094 | 924 | 0.8041 | - | - | - |
| 0.9104 | 925 | 0.6129 | - | - | - |
| 0.9114 | 926 | 0.8697 | - | - | - |
| 0.9124 | 927 | 0.7138 | - | - | - |
| 0.9134 | 928 | 1.0387 | - | - | - |
| 0.9144 | 929 | 0.6024 | - | - | - |
| 0.9154 | 930 | 0.6641 | - | - | - |
| 0.9163 | 931 | 0.8028 | - | - | - |
| 0.9173 | 932 | 0.8097 | - | - | - |
| 0.9183 | 933 | 0.6162 | - | - | - |
| 0.9193 | 934 | 0.4264 | - | - | - |
| 0.9203 | 935 | 0.3983 | - | - | - |
| 0.9213 | 936 | 0.7519 | - | - | - |
| 0.9222 | 937 | 1.0682 | - | - | - |
| 0.9232 | 938 | 0.6805 | - | - | - |
| 0.9242 | 939 | 1.1305 | - | - | - |
| 0.9252 | 940 | 1.5805 | - | - | - |
| 0.9262 | 941 | 0.7031 | - | - | - |
| 0.9272 | 942 | 0.6847 | - | - | - |
| 0.9281 | 943 | 0.3777 | - | - | - |
| 0.9291 | 944 | 0.7438 | - | - | - |
| 0.9301 | 945 | 1.1754 | - | - | - |
| 0.9311 | 946 | 0.6602 | - | - | - |
| 0.9321 | 947 | 1.2893 | - | - | - |
| 0.9331 | 948 | 0.8315 | - | - | - |
| 0.9341 | 949 | 1.0961 | - | - | - |
| 0.9350 | 950 | 0.7657 | - | - | - |
| 0.9360 | 951 | 0.8915 | - | - | - |
| 0.9370 | 952 | 0.6784 | - | - | - |
| 0.9380 | 953 | 0.6772 | - | - | - |
| 0.9390 | 954 | 0.9102 | - | - | - |
| 0.9400 | 955 | 0.8083 | - | - | - |
| 0.9409 | 956 | 0.5966 | - | - | - |
| 0.9419 | 957 | 1.06 | - | - | - |
| 0.9429 | 958 | 1.0412 | - | - | - |
| 0.9439 | 959 | 0.9467 | - | - | - |
| 0.9449 | 960 | 0.847 | - | - | - |
| 0.9459 | 961 | 0.875 | - | - | - |
| 0.9469 | 962 | 0.8303 | - | - | - |
| 0.9478 | 963 | 0.8641 | - | - | - |
| 0.9488 | 964 | 0.6343 | - | - | - |
| 0.9498 | 965 | 0.7566 | - | - | - |
| 0.9508 | 966 | 0.9767 | - | - | - |
| 0.9518 | 967 | 0.7518 | - | - | - |
| 0.9528 | 968 | 0.5381 | - | - | - |
| 0.9537 | 969 | 0.9959 | - | - | - |
| 0.9547 | 970 | 0.8374 | - | - | - |
| 0.9557 | 971 | 0.5459 | - | - | - |
| 0.9567 | 972 | 0.6633 | - | - | - |
| 0.9577 | 973 | 0.9526 | - | - | - |
| 0.9587 | 974 | 0.8487 | - | - | - |
| 0.9596 | 975 | 0.6572 | - | - | - |
| 0.9606 | 976 | 0.8039 | - | - | - |
| 0.9616 | 977 | 0.6213 | - | - | - |
| 0.9626 | 978 | 0.5483 | - | - | - |
| 0.9636 | 979 | 0.516 | - | - | - |
| 0.9646 | 980 | 0.8891 | - | - | - |
| 0.9656 | 981 | 0.7904 | - | - | - |
| 0.9665 | 982 | 1.2282 | - | - | - |
| 0.9675 | 983 | 1.0609 | - | - | - |
| 0.9685 | 984 | 0.8063 | - | - | - |
| 0.9695 | 985 | 0.5294 | - | - | - |
| 0.9705 | 986 | 0.7394 | - | - | - |
| 0.9715 | 987 | 0.5749 | - | - | - |
| 0.9724 | 988 | 0.9125 | - | - | - |
| 0.9734 | 989 | 0.961 | - | - | - |
| 0.9744 | 990 | 0.5947 | - | - | - |
| 0.9754 | 991 | 0.6246 | - | - | - |
| 0.9764 | 992 | 0.6492 | - | - | - |
| 0.9774 | 993 | 1.0508 | - | - | - |
| 0.9783 | 994 | 0.7613 | - | - | - |
| 0.9793 | 995 | 0.706 | - | - | - |
| 0.9803 | 996 | 0.9458 | - | - | - |
| 0.9813 | 997 | 0.836 | - | - | - |
| 0.9823 | 998 | 0.7472 | - | - | - |
| 0.9833 | 999 | 0.9071 | - | - | - |
| 0.9843 | 1000 | 1.0935 | - | - | - |
| 0.9852 | 1001 | 0.5822 | - | - | - |
| 0.9862 | 1002 | 0.6596 | - | - | - |
| 0.9872 | 1003 | 0.5536 | - | - | - |
| 0.9882 | 1004 | 1.0741 | - | - | - |
| 0.9892 | 1005 | 0.4586 | - | - | - |
| 0.9902 | 1006 | 0.9633 | - | - | - |
| 0.9911 | 1007 | 0.8739 | - | - | - |
| 0.9921 | 1008 | 0.665 | - | - | - |
| 0.9931 | 1009 | 0.9486 | - | - | - |
| 0.9941 | 1010 | 0.5323 | - | - | - |
| 0.9951 | 1011 | 0.6006 | - | - | - |
| 0.9961 | 1012 | 0.4568 | - | - | - |
| 0.9970 | 1013 | 0.7544 | - | - | - |
| 0.9980 | 1014 | 1.2437 | - | - | - |
| 0.9990 | 1015 | 0.8985 | - | - | - |
| 1.0 | 1016 | 0.3179 | - | - | - |
| 1.0010 | 1017 | 1.2519 | - | - | - |
| 1.0020 | 1018 | 0.9775 | - | - | - |
| 1.0030 | 1019 | 0.8967 | - | - | - |
| 1.0039 | 1020 | 0.5918 | - | - | - |
| 1.0049 | 1021 | 0.5798 | - | - | - |
| 1.0059 | 1022 | 0.5934 | - | - | - |
| 1.0069 | 1023 | 0.6872 | - | - | - |
| 1.0079 | 1024 | 0.9535 | - | - | - |
| 1.0089 | 1025 | 0.4967 | - | - | - |
| 1.0098 | 1026 | 1.116 | - | - | - |
| 1.0108 | 1027 | 1.0446 | - | - | - |
| 1.0118 | 1028 | 0.5189 | - | - | - |
| 1.0128 | 1029 | 0.8272 | - | - | - |
| 1.0138 | 1030 | 0.4901 | - | - | - |
| 1.0148 | 1031 | 0.8926 | - | - | - |
| 1.0157 | 1032 | 0.5543 | - | - | - |
| 1.0167 | 1033 | 0.2579 | - | - | - |
| 1.0177 | 1034 | 0.865 | - | - | - |
| 1.0187 | 1035 | 1.0559 | - | - | - |
| 1.0197 | 1036 | 0.714 | - | - | - |
| 1.0207 | 1037 | 0.5185 | - | - | - |
| 1.0217 | 1038 | 1.3209 | - | - | - |
| 1.0226 | 1039 | 0.3696 | - | - | - |
| 1.0236 | 1040 | 0.4839 | - | - | - |
| 1.0246 | 1041 | 0.7694 | - | - | - |
| 1.0256 | 1042 | 1.3417 | - | - | - |
| 1.0266 | 1043 | 0.8292 | - | - | - |
| 1.0276 | 1044 | 0.3835 | - | - | - |
| 1.0285 | 1045 | 0.3755 | - | - | - |
| 1.0295 | 1046 | 0.6396 | - | - | - |
| 1.0305 | 1047 | 0.364 | - | - | - |
| 1.0315 | 1048 | 0.9232 | - | - | - |
| 1.0325 | 1049 | 0.6706 | - | - | - |
| 1.0335 | 1050 | 0.8329 | - | - | - |
| 1.0344 | 1051 | 0.4093 | - | - | - |
| 1.0354 | 1052 | 0.7251 | - | - | - |
| 1.0364 | 1053 | 0.9254 | - | - | - |
| 1.0374 | 1054 | 0.6365 | - | - | - |
| 1.0384 | 1055 | 0.7136 | - | - | - |
| 1.0394 | 1056 | 0.6278 | - | - | - |
| 1.0404 | 1057 | 0.6769 | - | - | - |
| 1.0413 | 1058 | 0.7704 | - | - | - |
| 1.0423 | 1059 | 0.7701 | - | - | - |
| 1.0433 | 1060 | 0.9639 | - | - | - |
| 1.0443 | 1061 | 0.7518 | - | - | - |
| 1.0453 | 1062 | 0.7474 | - | - | - |
| 1.0463 | 1063 | 1.2196 | - | - | - |
| 1.0472 | 1064 | 1.1476 | - | - | - |
| 1.0482 | 1065 | 0.7139 | - | - | - |
| 1.0492 | 1066 | 1.0979 | - | - | - |
| 1.0502 | 1067 | 0.7113 | - | - | - |
| 1.0512 | 1068 | 0.6796 | - | - | - |
| 1.0522 | 1069 | 1.1551 | - | - | - |
| 1.0531 | 1070 | 0.7947 | - | - | - |
| 1.0541 | 1071 | 0.6783 | 0.6381 | 0.4883 | 0.7054 |
| 1.0551 | 1072 | 0.7295 | - | - | - |
| 1.0561 | 1073 | 0.4529 | - | - | - |
| 1.0571 | 1074 | 0.2625 | - | - | - |
| 1.0581 | 1075 | 1.2557 | - | - | - |
| 1.0591 | 1076 | 0.4826 | - | - | - |
| 1.0600 | 1077 | 1.2309 | - | - | - |
| 1.0610 | 1078 | 0.4545 | - | - | - |
| 1.0620 | 1079 | 0.6658 | - | - | - |
| 1.0630 | 1080 | 0.8651 | - | - | - |
| 1.0640 | 1081 | 1.0702 | - | - | - |
| 1.0650 | 1082 | 1.0225 | - | - | - |
| 1.0659 | 1083 | 0.6952 | - | - | - |
| 1.0669 | 1084 | 1.0918 | - | - | - |
| 1.0679 | 1085 | 0.5222 | - | - | - |
| 1.0689 | 1086 | 1.1311 | - | - | - |
| 1.0699 | 1087 | 0.6464 | - | - | - |
| 1.0709 | 1088 | 0.801 | - | - | - |
| 1.0719 | 1089 | 0.3743 | - | - | - |
| 1.0728 | 1090 | 0.6204 | - | - | - |
| 1.0738 | 1091 | 0.5369 | - | - | - |
| 1.0748 | 1092 | 0.6895 | - | - | - |
| 1.0758 | 1093 | 1.2127 | - | - | - |
| 1.0768 | 1094 | 0.8397 | - | - | - |
| 1.0778 | 1095 | 0.3694 | - | - | - |
| 1.0787 | 1096 | 0.7576 | - | - | - |
| 1.0797 | 1097 | 0.9494 | - | - | - |
| 1.0807 | 1098 | 0.8477 | - | - | - |
| 1.0817 | 1099 | 0.4869 | - | - | - |
| 1.0827 | 1100 | 0.6753 | - | - | - |
| 1.0837 | 1101 | 0.7351 | - | - | - |
| 1.0846 | 1102 | 0.8257 | - | - | - |
| 1.0856 | 1103 | 1.144 | - | - | - |
| 1.0866 | 1104 | 0.5526 | - | - | - |
| 1.0876 | 1105 | 0.6686 | - | - | - |
| 1.0886 | 1106 | 0.7683 | - | - | - |
| 1.0896 | 1107 | 0.3337 | - | - | - |
| 1.0906 | 1108 | 0.8686 | - | - | - |
| 1.0915 | 1109 | 0.66 | - | - | - |
| 1.0925 | 1110 | 0.9329 | - | - | - |
| 1.0935 | 1111 | 0.5129 | - | - | - |
| 1.0945 | 1112 | 0.8907 | - | - | - |
| 1.0955 | 1113 | 0.6305 | - | - | - |
| 1.0965 | 1114 | 0.3746 | - | - | - |
| 1.0974 | 1115 | 0.6791 | - | - | - |
| 1.0984 | 1116 | 1.4172 | - | - | - |
| 1.0994 | 1117 | 0.5184 | - | - | - |
| 1.1004 | 1118 | 0.4803 | - | - | - |
| 1.1014 | 1119 | 0.647 | - | - | - |
| 1.1024 | 1120 | 0.3867 | - | - | - |
| 1.1033 | 1121 | 0.4965 | - | - | - |
| 1.1043 | 1122 | 0.9508 | - | - | - |
| 1.1053 | 1123 | 0.709 | - | - | - |
| 1.1063 | 1124 | 0.9625 | - | - | - |
| 1.1073 | 1125 | 0.7724 | - | - | - |
| 1.1083 | 1126 | 0.4318 | - | - | - |
| 1.1093 | 1127 | 0.6653 | - | - | - |
| 1.1102 | 1128 | 0.781 | - | - | - |
| 1.1112 | 1129 | 0.6985 | - | - | - |
| 1.1122 | 1130 | 1.2949 | - | - | - |
| 1.1132 | 1131 | 0.6845 | - | - | - |
| 1.1142 | 1132 | 0.7022 | - | - | - |
| 1.1152 | 1133 | 0.8645 | - | - | - |
| 1.1161 | 1134 | 0.5331 | - | - | - |
| 1.1171 | 1135 | 0.5636 | - | - | - |
| 1.1181 | 1136 | 0.4511 | - | - | - |
| 1.1191 | 1137 | 0.605 | - | - | - |
| 1.1201 | 1138 | 0.6367 | - | - | - |
| 1.1211 | 1139 | 1.1988 | - | - | - |
| 1.1220 | 1140 | 0.5973 | - | - | - |
| 1.1230 | 1141 | 0.8703 | - | - | - |
| 1.1240 | 1142 | 0.48 | - | - | - |
| 1.125 | 1143 | 0.8903 | - | - | - |
| 1.1260 | 1144 | 0.6978 | - | - | - |
| 1.1270 | 1145 | 0.8008 | - | - | - |
| 1.1280 | 1146 | 0.9583 | - | - | - |
| 1.1289 | 1147 | 0.5823 | - | - | - |
| 1.1299 | 1148 | 0.974 | - | - | - |
| 1.1309 | 1149 | 1.1149 | - | - | - |
| 1.1319 | 1150 | 0.5558 | - | - | - |
| 1.1329 | 1151 | 0.9106 | - | - | - |
| 1.1339 | 1152 | 0.671 | - | - | - |
| 1.1348 | 1153 | 0.9424 | - | - | - |
| 1.1358 | 1154 | 0.6605 | - | - | - |
| 1.1368 | 1155 | 0.536 | - | - | - |
| 1.1378 | 1156 | 0.38 | - | - | - |
| 1.1388 | 1157 | 0.6255 | - | - | - |
| 1.1398 | 1158 | 1.435 | - | - | - |
| 1.1407 | 1159 | 0.5903 | - | - | - |
| 1.1417 | 1160 | 0.9517 | - | - | - |
| 1.1427 | 1161 | 0.4636 | - | - | - |
| 1.1437 | 1162 | 0.3721 | - | - | - |
| 1.1447 | 1163 | 0.6832 | - | - | - |
| 1.1457 | 1164 | 0.5893 | - | - | - |
| 1.1467 | 1165 | 0.6226 | - | - | - |
| 1.1476 | 1166 | 0.5715 | - | - | - |
| 1.1486 | 1167 | 1.0958 | - | - | - |
| 1.1496 | 1168 | 0.689 | - | - | - |
| 1.1506 | 1169 | 0.6443 | - | - | - |
| 1.1516 | 1170 | 0.9278 | - | - | - |
| 1.1526 | 1171 | 0.7009 | - | - | - |
| 1.1535 | 1172 | 0.6254 | - | - | - |
| 1.1545 | 1173 | 0.7537 | - | - | - |
| 1.1555 | 1174 | 0.7559 | - | - | - |
| 1.1565 | 1175 | 0.8148 | - | - | - |
| 1.1575 | 1176 | 0.2994 | - | - | - |
| 1.1585 | 1177 | 0.2148 | - | - | - |
| 1.1594 | 1178 | 1.0492 | - | - | - |
| 1.1604 | 1179 | 0.5191 | - | - | - |
| 1.1614 | 1180 | 1.3508 | - | - | - |
| 1.1624 | 1181 | 1.0396 | - | - | - |
| 1.1634 | 1182 | 0.5003 | - | - | - |
| 1.1644 | 1183 | 0.7736 | - | - | - |
| 1.1654 | 1184 | 0.3263 | - | - | - |
| 1.1663 | 1185 | 1.2059 | - | - | - |
| 1.1673 | 1186 | 1.3514 | - | - | - |
| 1.1683 | 1187 | 0.9086 | - | - | - |
| 1.1693 | 1188 | 0.7245 | - | - | - |
| 1.1703 | 1189 | 0.717 | - | - | - |
| 1.1713 | 1190 | 0.6741 | - | - | - |
| 1.1722 | 1191 | 1.2695 | - | - | - |
| 1.1732 | 1192 | 0.406 | - | - | - |
| 1.1742 | 1193 | 0.5408 | - | - | - |
| 1.1752 | 1194 | 0.4256 | - | - | - |
| 1.1762 | 1195 | 0.4827 | - | - | - |
| 1.1772 | 1196 | 0.5621 | - | - | - |
| 1.1781 | 1197 | 0.6734 | - | - | - |
| 1.1791 | 1198 | 0.4685 | - | - | - |
| 1.1801 | 1199 | 0.859 | - | - | - |
| 1.1811 | 1200 | 1.4388 | - | - | - |
| 1.1821 | 1201 | 1.1846 | - | - | - |
| 1.1831 | 1202 | 0.6824 | - | - | - |
| 1.1841 | 1203 | 1.2064 | - | - | - |
| 1.1850 | 1204 | 0.5668 | - | - | - |
| 1.1860 | 1205 | 0.5286 | - | - | - |
| 1.1870 | 1206 | 0.6316 | - | - | - |
| 1.1880 | 1207 | 0.8011 | - | - | - |
| 1.1890 | 1208 | 0.66 | - | - | - |
| 1.1900 | 1209 | 0.3735 | - | - | - |
| 1.1909 | 1210 | 0.7461 | - | - | - |
| 1.1919 | 1211 | 0.5508 | - | - | - |
| 1.1929 | 1212 | 0.6379 | - | - | - |
| 1.1939 | 1213 | 0.5204 | - | - | - |
| 1.1949 | 1214 | 0.7522 | - | - | - |
| 1.1959 | 1215 | 0.9415 | - | - | - |
| 1.1969 | 1216 | 0.6351 | - | - | - |
| 1.1978 | 1217 | 0.262 | - | - | - |
| 1.1988 | 1218 | 0.9048 | - | - | - |
| 1.1998 | 1219 | 0.6562 | - | - | - |
| 1.2008 | 1220 | 0.4502 | - | - | - |
</details>
### Framework Versions
- Python: 3.10.12
- Sentence Transformers: 3.2.1
- Transformers: 4.44.2
- PyTorch: 2.5.0+cu121
- Accelerate: 0.34.2
- Datasets: 3.0.2
- 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",
}
```
#### GISTEmbedLoss
```bibtex
@misc{solatorio2024gistembed,
title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
author={Aivin V. Solatorio},
year={2024},
eprint={2402.16829},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
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