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--- |
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library_name: setfit |
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tags: |
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- setfit |
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- absa |
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- sentence-transformers |
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- text-classification |
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- generated_from_setfit_trainer |
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base_model: sentence-transformers/all-MiniLM-L6-v2 |
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metrics: |
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- accuracy |
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widget: |
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- text: netbook:I am not going to sit here and complain about it not having a cd drive |
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and what not because it is a netbook, it is made to be compact and if you want |
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all the other stuff get a laptop. |
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- text: price:I finally decided on this laptop because it was the right price for |
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what I need it. |
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- text: shipped:This laptop looked brand new and was shipped very quickly. |
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- text: business:They offer the best warranty in the business, and don't 3rd party |
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it out like Toshiba. |
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- text: email:My husband uses it mostly for games, email and music. |
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pipeline_tag: text-classification |
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inference: false |
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model-index: |
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- name: SetFit Aspect Model with sentence-transformers/all-MiniLM-L6-v2 |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: Unknown |
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type: unknown |
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split: test |
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metrics: |
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- type: accuracy |
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value: 0.8947936336660373 |
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name: Accuracy |
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--- |
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# SetFit Aspect Model with sentence-transformers/all-MiniLM-L6-v2 |
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Aspect Based Sentiment Analysis (ABSA). This SetFit model uses [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. In particular, this model is in charge of filtering aspect span candidates. |
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The model has been trained using an efficient few-shot learning technique that involves: |
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. |
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2. Training a classification head with features from the fine-tuned Sentence Transformer. |
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This model was trained within the context of a larger system for ABSA, which looks like so: |
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1. Use a spaCy model to select possible aspect span candidates. |
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2. **Use this SetFit model to filter these possible aspect span candidates.** |
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3. Use a SetFit model to classify the filtered aspect span candidates. |
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## Model Details |
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### Model Description |
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- **Model Type:** SetFit |
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- **Sentence Transformer body:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) |
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- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance |
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- **spaCy Model:** en_core_web_sm |
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- **SetFitABSA Aspect Model:** [marcelomoreno26/all-MiniLM-L6-v2-absa-aspect2](https://huggingface.co/marcelomoreno26/all-MiniLM-L6-v2-absa-aspect2) |
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- **SetFitABSA Polarity Model:** [setfit-absa-polarity](https://huggingface.co/setfit-absa-polarity) |
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- **Maximum Sequence Length:** 256 tokens |
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- **Number of Classes:** 2 classes |
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) --> |
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<!-- - **Language:** Unknown --> |
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<!-- - **License:** Unknown --> |
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### Model Sources |
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) |
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) |
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) |
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### Model Labels |
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| Label | Examples | |
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|:----------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
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| aspect | <ul><li>'cord:I charge it at night and skip taking the cord with me because of the good battery life.'</li><li>'battery life:I charge it at night and skip taking the cord with me because of the good battery life.'</li><li>'service center:The tech guy then said the service center does not do 1-to-1 exchange and I have to direct my concern to the "sales" team, which is the retail shop which I bought my netbook from.'</li></ul> | |
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| no aspect | <ul><li>'night:I charge it at night and skip taking the cord with me because of the good battery life.'</li><li>'skip:I charge it at night and skip taking the cord with me because of the good battery life.'</li><li>'exchange:The tech guy then said the service center does not do 1-to-1 exchange and I have to direct my concern to the "sales" team, which is the retail shop which I bought my netbook from.'</li></ul> | |
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## Evaluation |
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### Metrics |
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| Label | Accuracy | |
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|:--------|:---------| |
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| **all** | 0.8948 | |
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## Uses |
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### Direct Use for Inference |
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First install the SetFit library: |
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```bash |
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pip install setfit |
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``` |
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Then you can load this model and run inference. |
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```python |
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from setfit import AbsaModel |
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# Download from the 🤗 Hub |
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model = AbsaModel.from_pretrained( |
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"marcelomoreno26/all-MiniLM-L6-v2-absa-aspect2", |
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"setfit-absa-polarity", |
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) |
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# Run inference |
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preds = model("The food was great, but the venue is just way too busy.") |
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``` |
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<!-- |
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### Downstream Use |
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*List how someone could finetune this model on their own dataset.* |
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--> |
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<!-- |
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### Out-of-Scope Use |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
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--> |
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<!-- |
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## Bias, Risks and Limitations |
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
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--> |
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<!-- |
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### Recommendations |
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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--> |
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## Training Details |
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### Training Set Metrics |
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| Training set | Min | Median | Max | |
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|:-------------|:----|:--------|:----| |
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| Word count | 2 | 21.9670 | 75 | |
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| Label | Training Sample Count | |
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|:----------|:----------------------| |
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| no aspect | 690 | |
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| aspect | 644 | |
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### Training Hyperparameters |
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- batch_size: (16, 2) |
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- num_epochs: (1, 16) |
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- max_steps: -1 |
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- sampling_strategy: oversampling |
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- body_learning_rate: (2e-05, 1e-05) |
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- head_learning_rate: 0.01 |
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- loss: CosineSimilarityLoss |
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- distance_metric: cosine_distance |
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- margin: 0.25 |
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- end_to_end: False |
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- use_amp: False |
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- warmup_proportion: 0.1 |
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- seed: 42 |
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- eval_max_steps: -1 |
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- load_best_model_at_end: False |
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### Training Results |
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| Epoch | Step | Training Loss | Validation Loss | |
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|:------:|:-----:|:-------------:|:---------------:| |
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| 0.0000 | 1 | 0.3662 | - | |
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| 0.0015 | 50 | 0.3374 | - | |
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| 0.0029 | 100 | 0.3411 | - | |
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| 0.0044 | 150 | 0.2945 | - | |
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| 0.0059 | 200 | 0.2944 | - | |
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| 0.0073 | 250 | 0.2942 | - | |
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| 0.0088 | 300 | 0.2409 | - | |
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| 0.0103 | 350 | 0.2817 | - | |
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| 0.0118 | 400 | 0.3149 | - | |
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| 0.0132 | 450 | 0.2618 | - | |
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| 0.0147 | 500 | 0.247 | - | |
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| 0.0162 | 550 | 0.2883 | - | |
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| 0.0176 | 600 | 0.2783 | - | |
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| 0.0191 | 650 | 0.2418 | - | |
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| 0.0206 | 700 | 0.2938 | - | |
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| 0.0220 | 750 | 0.2376 | - | |
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| 0.0235 | 800 | 0.2652 | - | |
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| 0.0250 | 850 | 0.2442 | - | |
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| 0.0265 | 900 | 0.2678 | - | |
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| 0.0279 | 950 | 0.2216 | - | |
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| 0.0294 | 1000 | 0.1816 | - | |
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| 0.0309 | 1050 | 0.1102 | - | |
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| 0.0323 | 1100 | 0.2985 | - | |
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| 0.0338 | 1150 | 0.1124 | - | |
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| 0.0353 | 1200 | 0.1075 | - | |
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| 0.0367 | 1250 | 0.0819 | - | |
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| 0.0382 | 1300 | 0.1238 | - | |
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| 0.0397 | 1350 | 0.0529 | - | |
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| 0.0412 | 1400 | 0.026 | - | |
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| 0.0426 | 1450 | 0.0289 | - | |
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| 0.0441 | 1500 | 0.067 | - | |
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| 0.0456 | 1550 | 0.0276 | - | |
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| 0.0470 | 1600 | 0.0162 | - | |
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| 0.0485 | 1650 | 0.0083 | - | |
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| 0.0500 | 1700 | 0.0017 | - | |
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| 0.0514 | 1750 | 0.0028 | - | |
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| 0.0529 | 1800 | 0.0045 | - | |
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| 0.0544 | 1850 | 0.0022 | - | |
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| 0.0558 | 1900 | 0.0014 | - | |
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| 0.0573 | 1950 | 0.0059 | - | |
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| 0.0588 | 2000 | 0.0019 | - | |
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| 0.0603 | 2050 | 0.0014 | - | |
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| 0.0617 | 2100 | 0.0022 | - | |
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| 0.0632 | 2150 | 0.0005 | - | |
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| 0.0647 | 2200 | 0.0008 | - | |
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| 0.0661 | 2250 | 0.0005 | - | |
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| 0.0676 | 2300 | 0.0006 | - | |
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| 0.0691 | 2350 | 0.0003 | - | |
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| 0.0705 | 2400 | 0.0007 | - | |
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| 0.0720 | 2450 | 0.0005 | - | |
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| 0.0735 | 2500 | 0.0005 | - | |
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| 0.0750 | 2550 | 0.0612 | - | |
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| 0.0764 | 2600 | 0.0004 | - | |
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| 0.0779 | 2650 | 0.041 | - | |
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| 0.0794 | 2700 | 0.0002 | - | |
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| 0.0808 | 2750 | 0.0003 | - | |
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| 0.0823 | 2800 | 0.0002 | - | |
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| 0.0838 | 2850 | 0.0002 | - | |
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| 0.0852 | 2900 | 0.0002 | - | |
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| 0.0867 | 2950 | 0.0004 | - | |
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| 0.0882 | 3000 | 0.0006 | - | |
|
| 0.0897 | 3050 | 0.0601 | - | |
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| 0.0911 | 3100 | 0.0002 | - | |
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| 0.0926 | 3150 | 0.0108 | - | |
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| 0.0941 | 3200 | 0.0003 | - | |
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| 0.0955 | 3250 | 0.0363 | - | |
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| 0.0970 | 3300 | 0.0006 | - | |
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| 0.0985 | 3350 | 0.0002 | - | |
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| 0.0999 | 3400 | 0.0033 | - | |
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| 0.1014 | 3450 | 0.0002 | - | |
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| 0.1029 | 3500 | 0.0002 | - | |
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| 0.1044 | 3550 | 0.0006 | - | |
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| 0.1058 | 3600 | 0.0002 | - | |
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| 0.1073 | 3650 | 0.0002 | - | |
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| 0.1088 | 3700 | 0.0001 | - | |
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| 0.1102 | 3750 | 0.0002 | - | |
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| 0.1117 | 3800 | 0.0002 | - | |
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| 0.1132 | 3850 | 0.0004 | - | |
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| 0.1146 | 3900 | 0.0003 | - | |
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| 0.1161 | 3950 | 0.0001 | - | |
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| 0.1176 | 4000 | 0.0004 | - | |
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| 0.1190 | 4050 | 0.0003 | - | |
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| 0.1205 | 4100 | 0.001 | - | |
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| 0.1220 | 4150 | 0.0002 | - | |
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| 0.1235 | 4200 | 0.0001 | - | |
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| 0.1249 | 4250 | 0.0003 | - | |
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| 0.1264 | 4300 | 0.0003 | - | |
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| 0.1279 | 4350 | 0.0002 | - | |
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| 0.1293 | 4400 | 0.0001 | - | |
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| 0.1308 | 4450 | 0.0001 | - | |
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| 0.1323 | 4500 | 0.0001 | - | |
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| 0.1337 | 4550 | 0.0001 | - | |
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| 0.1352 | 4600 | 0.0001 | - | |
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| 0.1367 | 4650 | 0.0003 | - | |
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| 0.1382 | 4700 | 0.0006 | - | |
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| 0.1396 | 4750 | 0.0003 | - | |
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| 0.1411 | 4800 | 0.0001 | - | |
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| 0.1426 | 4850 | 0.0011 | - | |
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| 0.1440 | 4900 | 0.0001 | - | |
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| 0.1455 | 4950 | 0.0001 | - | |
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| 0.1470 | 5000 | 0.0001 | - | |
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| 0.1484 | 5050 | 0.0001 | - | |
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| 0.1499 | 5100 | 0.0002 | - | |
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| 0.1514 | 5150 | 0.0497 | - | |
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| 0.1529 | 5200 | 0.0002 | - | |
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| 0.1543 | 5250 | 0.0001 | - | |
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| 0.1558 | 5300 | 0.0008 | - | |
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| 0.1573 | 5350 | 0.0001 | - | |
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| 0.1587 | 5400 | 0.0002 | - | |
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| 0.1602 | 5450 | 0.0001 | - | |
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| 0.1617 | 5500 | 0.0003 | - | |
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| 0.1631 | 5550 | 0.0003 | - | |
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| 0.1646 | 5600 | 0.0004 | - | |
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| 0.1661 | 5650 | 0.0002 | - | |
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| 0.1675 | 5700 | 0.0002 | - | |
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| 0.1690 | 5750 | 0.0001 | - | |
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| 0.1705 | 5800 | 0.0001 | - | |
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| 0.1720 | 5850 | 0.0001 | - | |
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| 0.1734 | 5900 | 0.0004 | - | |
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| 0.1749 | 5950 | 0.0001 | - | |
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| 0.1764 | 6000 | 0.0001 | - | |
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| 0.1778 | 6050 | 0.0001 | - | |
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| 0.125 | 1 | 0.0002 | - | |
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| 0.5 | 4 | 0.0003 | - | |
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| 1.0 | 8 | 0.0 | - | |
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| 0.0000 | 1 | 0.0001 | - | |
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| 0.0015 | 50 | 0.0001 | - | |
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| 0.0029 | 100 | 0.0 | - | |
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| 0.0044 | 150 | 0.0001 | - | |
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| 0.125 | 1 | 0.0 | - | |
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| 0.5 | 4 | 0.0 | - | |
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| 0.0000 | 1 | 0.0003 | - | |
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| 0.0009 | 50 | 0.0003 | - | |
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| 0.0018 | 100 | 0.0003 | - | |
|
| 0.0027 | 150 | 0.0001 | - | |
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| 0.0036 | 200 | 0.0001 | - | |
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| 0.0045 | 250 | 0.1015 | - | |
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| 0.0054 | 300 | 0.0005 | - | |
|
| 0.0063 | 350 | 0.0579 | - | |
|
| 0.0072 | 400 | 0.0001 | - | |
|
| 0.0081 | 450 | 0.0897 | - | |
|
| 0.0090 | 500 | 0.0618 | - | |
|
| 0.0099 | 550 | 0.0002 | - | |
|
| 0.0108 | 600 | 0.0001 | - | |
|
| 0.0117 | 650 | 0.0004 | - | |
|
| 0.0126 | 700 | 0.0002 | - | |
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| 0.0135 | 750 | 0.0002 | - | |
|
| 0.0143 | 800 | 0.0001 | - | |
|
| 0.0152 | 850 | 0.062 | - | |
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| 0.0161 | 900 | 0.0004 | - | |
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| 0.0170 | 950 | 0.0002 | - | |
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| 0.0179 | 1000 | 0.0001 | - | |
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| 0.0188 | 1050 | 0.0628 | - | |
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| 0.0197 | 1100 | 0.0003 | - | |
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| 0.0206 | 1150 | 0.0003 | - | |
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| 0.0215 | 1200 | 0.0001 | - | |
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| 0.0224 | 1250 | 0.0001 | - | |
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| 0.0233 | 1300 | 0.0001 | - | |
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| 0.0000 | 1 | 0.0002 | - | |
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| 0.0009 | 50 | 0.0002 | - | |
|
| 0.0018 | 100 | 0.0001 | - | |
|
| 0.0027 | 150 | 0.0001 | - | |
|
| 0.0036 | 200 | 0.0001 | - | |
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| 0.0045 | 250 | 0.0002 | - | |
|
| 0.0054 | 300 | 0.0001 | - | |
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| 0.0063 | 350 | 0.0002 | - | |
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| 0.0072 | 400 | 0.0002 | - | |
|
| 0.0081 | 450 | 0.0262 | - | |
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| 0.0090 | 500 | 0.0001 | - | |
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| 0.0099 | 550 | 0.0002 | - | |
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| 0.0108 | 600 | 0.0001 | - | |
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| 0.0117 | 650 | 0.0001 | - | |
|
| 0.0126 | 700 | 0.0001 | - | |
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| 0.0135 | 750 | 0.0001 | - | |
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| 0.0143 | 800 | 0.0001 | - | |
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| 0.0152 | 850 | 0.0002 | - | |
|
| 0.0161 | 900 | 0.0001 | - | |
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| 0.0170 | 950 | 0.0001 | - | |
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| 0.0179 | 1000 | 0.0001 | - | |
|
| 0.0188 | 1050 | 0.06 | - | |
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| 0.0197 | 1100 | 0.0001 | - | |
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| 0.0206 | 1150 | 0.0001 | - | |
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| 0.0215 | 1200 | 0.0001 | - | |
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| 0.0224 | 1250 | 0.0001 | - | |
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| 0.0233 | 1300 | 0.0001 | - | |
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| 0.0242 | 1350 | 0.0001 | - | |
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| 0.0251 | 1400 | 0.0001 | - | |
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| 0.0260 | 1450 | 0.0001 | - | |
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| 0.0269 | 1500 | 0.0002 | - | |
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| 0.0278 | 1550 | 0.0001 | - | |
|
| 0.0287 | 1600 | 0.0001 | - | |
|
| 0.0296 | 1650 | 0.0125 | - | |
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| 0.0305 | 1700 | 0.0001 | - | |
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| 0.0314 | 1750 | 0.0001 | - | |
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| 0.0323 | 1800 | 0.0001 | - | |
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| 0.0332 | 1850 | 0.0001 | - | |
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| 0.0341 | 1900 | 0.0001 | - | |
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| 0.0350 | 1950 | 0.0001 | - | |
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| 0.0359 | 2000 | 0.0001 | - | |
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| 0.0368 | 2050 | 0.0001 | - | |
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| 0.0377 | 2100 | 0.0002 | - | |
|
| 0.0386 | 2150 | 0.0001 | - | |
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| 0.0395 | 2200 | 0.0001 | - | |
|
| 0.0404 | 2250 | 0.0407 | - | |
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| 0.0412 | 2300 | 0.0001 | - | |
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| 0.0421 | 2350 | 0.0001 | - | |
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| 0.0430 | 2400 | 0.0001 | - | |
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| 0.0439 | 2450 | 0.0001 | - | |
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| 0.0448 | 2500 | 0.0001 | - | |
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| 0.0457 | 2550 | 0.0 | - | |
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| 0.0466 | 2600 | 0.0 | - | |
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| 0.0475 | 2650 | 0.0001 | - | |
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| 0.0484 | 2700 | 0.0 | - | |
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| 0.0493 | 2750 | 0.0001 | - | |
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| 0.0502 | 2800 | 0.0001 | - | |
|
| 0.0511 | 2850 | 0.0001 | - | |
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| 0.0520 | 2900 | 0.0001 | - | |
|
| 0.0529 | 2950 | 0.0002 | - | |
|
| 0.0538 | 3000 | 0.0001 | - | |
|
| 0.0547 | 3050 | 0.0001 | - | |
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| 0.0556 | 3100 | 0.0001 | - | |
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| 0.0565 | 3150 | 0.0001 | - | |
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| 0.0574 | 3200 | 0.0 | - | |
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| 0.0583 | 3250 | 0.0 | - | |
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| 0.0592 | 3300 | 0.0 | - | |
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| 0.0601 | 3350 | 0.0001 | - | |
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| 0.0610 | 3400 | 0.0 | - | |
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| 0.0619 | 3450 | 0.0 | - | |
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| 0.0628 | 3500 | 0.0001 | - | |
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| 0.0637 | 3550 | 0.0001 | - | |
|
| 0.0646 | 3600 | 0.0 | - | |
|
| 0.0655 | 3650 | 0.0001 | - | |
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| 0.0664 | 3700 | 0.0 | - | |
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| 0.0673 | 3750 | 0.0001 | - | |
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| 0.0681 | 3800 | 0.0 | - | |
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| 0.0690 | 3850 | 0.0005 | - | |
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| 0.0699 | 3900 | 0.0001 | - | |
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| 0.0708 | 3950 | 0.0001 | - | |
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| 0.0717 | 4000 | 0.0 | - | |
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| 0.0726 | 4050 | 0.0001 | - | |
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| 0.0735 | 4100 | 0.0009 | - | |
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| 0.0744 | 4150 | 0.0001 | - | |
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| 0.0753 | 4200 | 0.0001 | - | |
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| 0.0762 | 4250 | 0.0001 | - | |
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| 0.0771 | 4300 | 0.0 | - | |
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| 0.0780 | 4350 | 0.0001 | - | |
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| 0.0789 | 4400 | 0.0001 | - | |
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| 0.0798 | 4450 | 0.0001 | - | |
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| 0.0807 | 4500 | 0.0 | - | |
|
| 0.0816 | 4550 | 0.0 | - | |
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| 0.0825 | 4600 | 0.0001 | - | |
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| 0.0834 | 4650 | 0.0 | - | |
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| 0.0843 | 4700 | 0.0 | - | |
|
| 0.0852 | 4750 | 0.0 | - | |
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| 0.0861 | 4800 | 0.0 | - | |
|
| 0.0870 | 4850 | 0.0 | - | |
|
| 0.0879 | 4900 | 0.0004 | - | |
|
| 0.0888 | 4950 | 0.0002 | - | |
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| 0.0897 | 5000 | 0.0001 | - | |
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| 0.0906 | 5050 | 0.0001 | - | |
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| 0.0915 | 5100 | 0.0 | - | |
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| 0.0924 | 5150 | 0.0026 | - | |
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| 0.0933 | 5200 | 0.0549 | - | |
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| 0.0942 | 5250 | 0.0001 | - | |
|
| 0.0950 | 5300 | 0.0011 | - | |
|
| 0.0959 | 5350 | 0.0 | - | |
|
| 0.0968 | 5400 | 0.0 | - | |
|
| 0.0977 | 5450 | 0.0 | - | |
|
| 0.0986 | 5500 | 0.0002 | - | |
|
| 0.0995 | 5550 | 0.0001 | - | |
|
| 0.1004 | 5600 | 0.0 | - | |
|
| 0.1013 | 5650 | 0.0001 | - | |
|
| 0.1022 | 5700 | 0.0001 | - | |
|
| 0.1031 | 5750 | 0.0 | - | |
|
| 0.1040 | 5800 | 0.0 | - | |
|
| 0.1049 | 5850 | 0.0 | - | |
|
| 0.1058 | 5900 | 0.0203 | - | |
|
| 0.1067 | 5950 | 0.0001 | - | |
|
| 0.1076 | 6000 | 0.0 | - | |
|
| 0.1085 | 6050 | 0.0 | - | |
|
| 0.1094 | 6100 | 0.0 | - | |
|
| 0.1103 | 6150 | 0.0 | - | |
|
| 0.1112 | 6200 | 0.0001 | - | |
|
| 0.1121 | 6250 | 0.0 | - | |
|
| 0.1130 | 6300 | 0.0 | - | |
|
| 0.1139 | 6350 | 0.0 | - | |
|
| 0.1148 | 6400 | 0.0 | - | |
|
| 0.1157 | 6450 | 0.0164 | - | |
|
| 0.1166 | 6500 | 0.0001 | - | |
|
| 0.1175 | 6550 | 0.0 | - | |
|
| 0.1184 | 6600 | 0.0001 | - | |
|
| 0.1193 | 6650 | 0.0002 | - | |
|
| 0.1202 | 6700 | 0.0001 | - | |
|
| 0.1211 | 6750 | 0.0 | - | |
|
| 0.1219 | 6800 | 0.0 | - | |
|
| 0.1228 | 6850 | 0.0 | - | |
|
| 0.1237 | 6900 | 0.0 | - | |
|
| 0.1246 | 6950 | 0.0 | - | |
|
| 0.1255 | 7000 | 0.0001 | - | |
|
| 0.1264 | 7050 | 0.0 | - | |
|
| 0.1273 | 7100 | 0.0 | - | |
|
| 0.1282 | 7150 | 0.0 | - | |
|
| 0.1291 | 7200 | 0.0002 | - | |
|
| 0.1300 | 7250 | 0.0 | - | |
|
| 0.1309 | 7300 | 0.0 | - | |
|
| 0.1318 | 7350 | 0.0 | - | |
|
| 0.1327 | 7400 | 0.0 | - | |
|
| 0.1336 | 7450 | 0.0 | - | |
|
| 0.1345 | 7500 | 0.0002 | - | |
|
| 0.1354 | 7550 | 0.0 | - | |
|
| 0.1363 | 7600 | 0.0 | - | |
|
| 0.1372 | 7650 | 0.0001 | - | |
|
| 0.1381 | 7700 | 0.0001 | - | |
|
| 0.1390 | 7750 | 0.0001 | - | |
|
| 0.1399 | 7800 | 0.0001 | - | |
|
| 0.1408 | 7850 | 0.0 | - | |
|
| 0.1417 | 7900 | 0.0 | - | |
|
| 0.1426 | 7950 | 0.0 | - | |
|
| 0.1435 | 8000 | 0.0142 | - | |
|
| 0.1444 | 8050 | 0.0001 | - | |
|
| 0.1453 | 8100 | 0.0 | - | |
|
| 0.1462 | 8150 | 0.0002 | - | |
|
| 0.1471 | 8200 | 0.0 | - | |
|
| 0.1480 | 8250 | 0.0 | - | |
|
| 0.1488 | 8300 | 0.0 | - | |
|
| 0.1497 | 8350 | 0.0 | - | |
|
| 0.1506 | 8400 | 0.0003 | - | |
|
| 0.1515 | 8450 | 0.0 | - | |
|
| 0.1524 | 8500 | 0.0 | - | |
|
| 0.1533 | 8550 | 0.0 | - | |
|
| 0.1542 | 8600 | 0.0 | - | |
|
| 0.1551 | 8650 | 0.0 | - | |
|
| 0.1560 | 8700 | 0.0 | - | |
|
| 0.1569 | 8750 | 0.0 | - | |
|
| 0.1578 | 8800 | 0.0 | - | |
|
| 0.1587 | 8850 | 0.0 | - | |
|
| 0.1596 | 8900 | 0.0 | - | |
|
| 0.1605 | 8950 | 0.0 | - | |
|
| 0.1614 | 9000 | 0.0 | - | |
|
| 0.1623 | 9050 | 0.0 | - | |
|
| 0.1632 | 9100 | 0.0 | - | |
|
| 0.1641 | 9150 | 0.0 | - | |
|
| 0.1650 | 9200 | 0.0 | - | |
|
| 0.1659 | 9250 | 0.0001 | - | |
|
| 0.1668 | 9300 | 0.0 | - | |
|
| 0.1677 | 9350 | 0.0 | - | |
|
| 0.1686 | 9400 | 0.0 | - | |
|
| 0.1695 | 9450 | 0.0 | - | |
|
| 0.1704 | 9500 | 0.0 | - | |
|
| 0.1713 | 9550 | 0.0 | - | |
|
| 0.1722 | 9600 | 0.0 | - | |
|
| 0.1731 | 9650 | 0.0 | - | |
|
| 0.1740 | 9700 | 0.0 | - | |
|
| 0.1749 | 9750 | 0.0 | - | |
|
| 0.1758 | 9800 | 0.0 | - | |
|
| 0.1766 | 9850 | 0.0 | - | |
|
| 0.1775 | 9900 | 0.0 | - | |
|
| 0.1784 | 9950 | 0.0 | - | |
|
| 0.1793 | 10000 | 0.0 | - | |
|
| 0.1802 | 10050 | 0.0097 | - | |
|
| 0.1811 | 10100 | 0.0 | - | |
|
| 0.1820 | 10150 | 0.0 | - | |
|
| 0.1829 | 10200 | 0.0 | - | |
|
| 0.1838 | 10250 | 0.0 | - | |
|
| 0.1847 | 10300 | 0.0001 | - | |
|
| 0.1856 | 10350 | 0.0 | - | |
|
| 0.1865 | 10400 | 0.0 | - | |
|
| 0.1874 | 10450 | 0.0 | - | |
|
| 0.1883 | 10500 | 0.0 | - | |
|
| 0.1892 | 10550 | 0.0 | - | |
|
| 0.1901 | 10600 | 0.0 | - | |
|
| 0.1910 | 10650 | 0.0 | - | |
|
| 0.1919 | 10700 | 0.0 | - | |
|
| 0.1928 | 10750 | 0.0 | - | |
|
| 0.1937 | 10800 | 0.0 | - | |
|
| 0.1946 | 10850 | 0.0 | - | |
|
| 0.1955 | 10900 | 0.0 | - | |
|
| 0.1964 | 10950 | 0.0 | - | |
|
| 0.1973 | 11000 | 0.0001 | - | |
|
| 0.1982 | 11050 | 0.0 | - | |
|
| 0.1991 | 11100 | 0.0 | - | |
|
| 0.2000 | 11150 | 0.0 | - | |
|
| 0.2009 | 11200 | 0.0 | - | |
|
| 0.2018 | 11250 | 0.0004 | - | |
|
| 0.2027 | 11300 | 0.0001 | - | |
|
| 0.2035 | 11350 | 0.0001 | - | |
|
| 0.2044 | 11400 | 0.0 | - | |
|
| 0.2053 | 11450 | 0.0001 | - | |
|
| 0.2062 | 11500 | 0.0 | - | |
|
| 0.2071 | 11550 | 0.0001 | - | |
|
| 0.2080 | 11600 | 0.0 | - | |
|
| 0.2089 | 11650 | 0.0 | - | |
|
| 0.2098 | 11700 | 0.0 | - | |
|
| 0.2107 | 11750 | 0.0 | - | |
|
| 0.2116 | 11800 | 0.0 | - | |
|
| 0.2125 | 11850 | 0.0 | - | |
|
| 0.2134 | 11900 | 0.0 | - | |
|
| 0.2143 | 11950 | 0.0001 | - | |
|
| 0.2152 | 12000 | 0.0 | - | |
|
| 0.2161 | 12050 | 0.0 | - | |
|
| 0.2170 | 12100 | 0.0 | - | |
|
| 0.2179 | 12150 | 0.0 | - | |
|
| 0.2188 | 12200 | 0.0 | - | |
|
| 0.2197 | 12250 | 0.0 | - | |
|
| 0.2206 | 12300 | 0.0 | - | |
|
| 0.2215 | 12350 | 0.0 | - | |
|
| 0.2224 | 12400 | 0.0 | - | |
|
| 0.2233 | 12450 | 0.0 | - | |
|
| 0.2242 | 12500 | 0.0 | - | |
|
| 0.2251 | 12550 | 0.0 | - | |
|
| 0.2260 | 12600 | 0.0 | - | |
|
| 0.2269 | 12650 | 0.0 | - | |
|
| 0.2278 | 12700 | 0.0 | - | |
|
| 0.2287 | 12750 | 0.0 | - | |
|
| 0.2296 | 12800 | 0.0 | - | |
|
| 0.2304 | 12850 | 0.0 | - | |
|
| 0.2313 | 12900 | 0.0 | - | |
|
| 0.2322 | 12950 | 0.0 | - | |
|
| 0.2331 | 13000 | 0.0 | - | |
|
| 0.2340 | 13050 | 0.0 | - | |
|
| 0.2349 | 13100 | 0.0 | - | |
|
| 0.2358 | 13150 | 0.0264 | - | |
|
| 0.2367 | 13200 | 0.0 | - | |
|
| 0.2376 | 13250 | 0.0 | - | |
|
| 0.2385 | 13300 | 0.0 | - | |
|
| 0.2394 | 13350 | 0.0 | - | |
|
| 0.2403 | 13400 | 0.0 | - | |
|
| 0.2412 | 13450 | 0.0 | - | |
|
| 0.2421 | 13500 | 0.0 | - | |
|
| 0.2430 | 13550 | 0.0 | - | |
|
| 0.2439 | 13600 | 0.0 | - | |
|
| 0.2448 | 13650 | 0.0 | - | |
|
| 0.2457 | 13700 | 0.0 | - | |
|
| 0.2466 | 13750 | 0.0 | - | |
|
| 0.2475 | 13800 | 0.0 | - | |
|
| 0.2484 | 13850 | 0.0 | - | |
|
| 0.2493 | 13900 | 0.0 | - | |
|
| 0.2502 | 13950 | 0.0 | - | |
|
| 0.2511 | 14000 | 0.0 | - | |
|
| 0.2520 | 14050 | 0.0 | - | |
|
| 0.2529 | 14100 | 0.0 | - | |
|
| 0.2538 | 14150 | 0.0001 | - | |
|
| 0.2547 | 14200 | 0.0 | - | |
|
| 0.2556 | 14250 | 0.0 | - | |
|
| 0.2565 | 14300 | 0.0 | - | |
|
| 0.2573 | 14350 | 0.0 | - | |
|
| 0.2582 | 14400 | 0.0 | - | |
|
| 0.2591 | 14450 | 0.0 | - | |
|
| 0.2600 | 14500 | 0.0 | - | |
|
| 0.2609 | 14550 | 0.0001 | - | |
|
| 0.2618 | 14600 | 0.0 | - | |
|
| 0.2627 | 14650 | 0.0 | - | |
|
| 0.2636 | 14700 | 0.0 | - | |
|
| 0.2645 | 14750 | 0.0 | - | |
|
| 0.2654 | 14800 | 0.0 | - | |
|
| 0.2663 | 14850 | 0.0 | - | |
|
| 0.2672 | 14900 | 0.0 | - | |
|
| 0.2681 | 14950 | 0.0001 | - | |
|
| 0.2690 | 15000 | 0.0 | - | |
|
| 0.2699 | 15050 | 0.0 | - | |
|
| 0.2708 | 15100 | 0.0 | - | |
|
| 0.2717 | 15150 | 0.0 | - | |
|
| 0.2726 | 15200 | 0.0 | - | |
|
| 0.2735 | 15250 | 0.0 | - | |
|
| 0.2744 | 15300 | 0.0 | - | |
|
| 0.2753 | 15350 | 0.0 | - | |
|
| 0.2762 | 15400 | 0.0 | - | |
|
| 0.2771 | 15450 | 0.0 | - | |
|
| 0.2780 | 15500 | 0.0001 | - | |
|
| 0.2789 | 15550 | 0.0621 | - | |
|
| 0.2798 | 15600 | 0.0056 | - | |
|
| 0.2807 | 15650 | 0.0 | - | |
|
| 0.2816 | 15700 | 0.0 | - | |
|
| 0.2825 | 15750 | 0.0145 | - | |
|
| 0.2834 | 15800 | 0.0 | - | |
|
| 0.2842 | 15850 | 0.0 | - | |
|
| 0.2851 | 15900 | 0.0166 | - | |
|
| 0.2860 | 15950 | 0.0 | - | |
|
| 0.2869 | 16000 | 0.0 | - | |
|
| 0.2878 | 16050 | 0.0 | - | |
|
| 0.2887 | 16100 | 0.0166 | - | |
|
| 0.2896 | 16150 | 0.0 | - | |
|
| 0.2905 | 16200 | 0.0 | - | |
|
| 0.2914 | 16250 | 0.0169 | - | |
|
| 0.2923 | 16300 | 0.0 | - | |
|
| 0.2932 | 16350 | 0.0 | - | |
|
| 0.2941 | 16400 | 0.0 | - | |
|
| 0.2950 | 16450 | 0.0 | - | |
|
| 0.2959 | 16500 | 0.0 | - | |
|
| 0.2968 | 16550 | 0.0 | - | |
|
| 0.2977 | 16600 | 0.0 | - | |
|
| 0.2986 | 16650 | 0.0 | - | |
|
| 0.2995 | 16700 | 0.0 | - | |
|
| 0.3004 | 16750 | 0.0 | - | |
|
| 0.3013 | 16800 | 0.0 | - | |
|
| 0.3022 | 16850 | 0.0 | - | |
|
| 0.3031 | 16900 | 0.0 | - | |
|
| 0.3040 | 16950 | 0.0 | - | |
|
| 0.3049 | 17000 | 0.0 | - | |
|
| 0.3058 | 17050 | 0.0138 | - | |
|
| 0.3067 | 17100 | 0.0 | - | |
|
| 0.3076 | 17150 | 0.0 | - | |
|
| 0.3085 | 17200 | 0.0 | - | |
|
| 0.3094 | 17250 | 0.0 | - | |
|
| 0.3103 | 17300 | 0.0 | - | |
|
| 0.3111 | 17350 | 0.0 | - | |
|
| 0.3120 | 17400 | 0.0 | - | |
|
| 0.3129 | 17450 | 0.0001 | - | |
|
| 0.3138 | 17500 | 0.0 | - | |
|
| 0.3147 | 17550 | 0.0 | - | |
|
| 0.3156 | 17600 | 0.0 | - | |
|
| 0.3165 | 17650 | 0.0 | - | |
|
| 0.3174 | 17700 | 0.0 | - | |
|
| 0.3183 | 17750 | 0.0 | - | |
|
| 0.3192 | 17800 | 0.0 | - | |
|
| 0.3201 | 17850 | 0.0 | - | |
|
| 0.3210 | 17900 | 0.0 | - | |
|
| 0.3219 | 17950 | 0.0001 | - | |
|
| 0.3228 | 18000 | 0.0 | - | |
|
| 0.3237 | 18050 | 0.0 | - | |
|
| 0.3246 | 18100 | 0.0 | - | |
|
| 0.3255 | 18150 | 0.0 | - | |
|
| 0.3264 | 18200 | 0.0 | - | |
|
| 0.3273 | 18250 | 0.0 | - | |
|
| 0.3282 | 18300 | 0.0 | - | |
|
| 0.3291 | 18350 | 0.0 | - | |
|
| 0.3300 | 18400 | 0.0 | - | |
|
| 0.3309 | 18450 | 0.0003 | - | |
|
| 0.3318 | 18500 | 0.0 | - | |
|
| 0.3327 | 18550 | 0.0 | - | |
|
| 0.3336 | 18600 | 0.0 | - | |
|
| 0.3345 | 18650 | 0.0 | - | |
|
| 0.3354 | 18700 | 0.0 | - | |
|
| 0.3363 | 18750 | 0.0 | - | |
|
| 0.3372 | 18800 | 0.0 | - | |
|
| 0.3380 | 18850 | 0.0 | - | |
|
| 0.3389 | 18900 | 0.0 | - | |
|
| 0.3398 | 18950 | 0.0 | - | |
|
| 0.3407 | 19000 | 0.0 | - | |
|
| 0.3416 | 19050 | 0.0 | - | |
|
| 0.3425 | 19100 | 0.0 | - | |
|
| 0.3434 | 19150 | 0.0 | - | |
|
| 0.3443 | 19200 | 0.0 | - | |
|
| 0.3452 | 19250 | 0.0 | - | |
|
| 0.3461 | 19300 | 0.0 | - | |
|
| 0.3470 | 19350 | 0.0 | - | |
|
| 0.3479 | 19400 | 0.0 | - | |
|
| 0.3488 | 19450 | 0.0 | - | |
|
| 0.3497 | 19500 | 0.0001 | - | |
|
| 0.3506 | 19550 | 0.0131 | - | |
|
| 0.3515 | 19600 | 0.0 | - | |
|
| 0.3524 | 19650 | 0.0 | - | |
|
| 0.3533 | 19700 | 0.0 | - | |
|
| 0.3542 | 19750 | 0.0 | - | |
|
| 0.3551 | 19800 | 0.0 | - | |
|
| 0.3560 | 19850 | 0.0 | - | |
|
| 0.3569 | 19900 | 0.0 | - | |
|
| 0.3578 | 19950 | 0.0 | - | |
|
| 0.3587 | 20000 | 0.0 | - | |
|
| 0.3596 | 20050 | 0.0 | - | |
|
| 0.3605 | 20100 | 0.0 | - | |
|
| 0.3614 | 20150 | 0.0 | - | |
|
| 0.3623 | 20200 | 0.0208 | - | |
|
| 0.3632 | 20250 | 0.0 | - | |
|
| 0.3641 | 20300 | 0.0 | - | |
|
| 0.3650 | 20350 | 0.0 | - | |
|
| 0.3658 | 20400 | 0.0 | - | |
|
| 0.3667 | 20450 | 0.0 | - | |
|
| 0.3676 | 20500 | 0.0 | - | |
|
| 0.3685 | 20550 | 0.0 | - | |
|
| 0.3694 | 20600 | 0.0 | - | |
|
| 0.3703 | 20650 | 0.0 | - | |
|
| 0.3712 | 20700 | 0.0 | - | |
|
| 0.3721 | 20750 | 0.0 | - | |
|
| 0.3730 | 20800 | 0.0 | - | |
|
| 0.3739 | 20850 | 0.0 | - | |
|
| 0.3748 | 20900 | 0.0 | - | |
|
| 0.3757 | 20950 | 0.0 | - | |
|
| 0.3766 | 21000 | 0.0 | - | |
|
| 0.3775 | 21050 | 0.0 | - | |
|
| 0.3784 | 21100 | 0.0 | - | |
|
| 0.3793 | 21150 | 0.0 | - | |
|
| 0.3802 | 21200 | 0.0 | - | |
|
| 0.3811 | 21250 | 0.0 | - | |
|
| 0.3820 | 21300 | 0.0 | - | |
|
| 0.3829 | 21350 | 0.0 | - | |
|
| 0.3838 | 21400 | 0.0 | - | |
|
| 0.3847 | 21450 | 0.0 | - | |
|
| 0.3856 | 21500 | 0.0 | - | |
|
| 0.3865 | 21550 | 0.0 | - | |
|
| 0.3874 | 21600 | 0.0 | - | |
|
| 0.3883 | 21650 | 0.0 | - | |
|
| 0.3892 | 21700 | 0.0 | - | |
|
| 0.3901 | 21750 | 0.0 | - | |
|
| 0.3910 | 21800 | 0.0 | - | |
|
| 0.3919 | 21850 | 0.0001 | - | |
|
| 0.3927 | 21900 | 0.0 | - | |
|
| 0.3936 | 21950 | 0.0 | - | |
|
| 0.3945 | 22000 | 0.0 | - | |
|
| 0.3954 | 22050 | 0.0 | - | |
|
| 0.3963 | 22100 | 0.0 | - | |
|
| 0.3972 | 22150 | 0.0 | - | |
|
| 0.3981 | 22200 | 0.0 | - | |
|
| 0.3990 | 22250 | 0.0 | - | |
|
| 0.3999 | 22300 | 0.0 | - | |
|
| 0.4008 | 22350 | 0.0 | - | |
|
| 0.4017 | 22400 | 0.0 | - | |
|
| 0.4026 | 22450 | 0.0 | - | |
|
| 0.4035 | 22500 | 0.0 | - | |
|
| 0.4044 | 22550 | 0.0 | - | |
|
| 0.4053 | 22600 | 0.0217 | - | |
|
| 0.4062 | 22650 | 0.0 | - | |
|
| 0.4071 | 22700 | 0.0 | - | |
|
| 0.4080 | 22750 | 0.0 | - | |
|
| 0.4089 | 22800 | 0.0 | - | |
|
| 0.4098 | 22850 | 0.0 | - | |
|
| 0.4107 | 22900 | 0.0 | - | |
|
| 0.4116 | 22950 | 0.0 | - | |
|
| 0.4125 | 23000 | 0.0 | - | |
|
| 0.4134 | 23050 | 0.0 | - | |
|
| 0.4143 | 23100 | 0.0 | - | |
|
| 0.4152 | 23150 | 0.0 | - | |
|
| 0.4161 | 23200 | 0.0 | - | |
|
| 0.4170 | 23250 | 0.0 | - | |
|
| 0.4179 | 23300 | 0.0 | - | |
|
| 0.4188 | 23350 | 0.0 | - | |
|
| 0.4196 | 23400 | 0.0 | - | |
|
| 0.4205 | 23450 | 0.0 | - | |
|
| 0.4214 | 23500 | 0.0 | - | |
|
| 0.4223 | 23550 | 0.0 | - | |
|
| 0.4232 | 23600 | 0.0 | - | |
|
| 0.4241 | 23650 | 0.0 | - | |
|
| 0.4250 | 23700 | 0.0 | - | |
|
| 0.4259 | 23750 | 0.0 | - | |
|
| 0.4268 | 23800 | 0.0 | - | |
|
| 0.4277 | 23850 | 0.0 | - | |
|
| 0.4286 | 23900 | 0.0098 | - | |
|
| 0.4295 | 23950 | 0.0 | - | |
|
| 0.4304 | 24000 | 0.0 | - | |
|
| 0.4313 | 24050 | 0.0 | - | |
|
| 0.4322 | 24100 | 0.0 | - | |
|
| 0.4331 | 24150 | 0.0 | - | |
|
| 0.4340 | 24200 | 0.0 | - | |
|
| 0.4349 | 24250 | 0.0 | - | |
|
| 0.4358 | 24300 | 0.0089 | - | |
|
| 0.4367 | 24350 | 0.0 | - | |
|
| 0.4376 | 24400 | 0.0 | - | |
|
| 0.4385 | 24450 | 0.0 | - | |
|
| 0.4394 | 24500 | 0.0 | - | |
|
| 0.4403 | 24550 | 0.0 | - | |
|
| 0.4412 | 24600 | 0.0092 | - | |
|
| 0.4421 | 24650 | 0.0003 | - | |
|
| 0.4430 | 24700 | 0.0283 | - | |
|
| 0.4439 | 24750 | 0.0 | - | |
|
| 0.4448 | 24800 | 0.0 | - | |
|
| 0.4457 | 24850 | 0.0 | - | |
|
| 0.4465 | 24900 | 0.0 | - | |
|
| 0.4474 | 24950 | 0.0 | - | |
|
| 0.4483 | 25000 | 0.0 | - | |
|
| 0.4492 | 25050 | 0.0 | - | |
|
| 0.4501 | 25100 | 0.0 | - | |
|
| 0.4510 | 25150 | 0.0002 | - | |
|
| 0.4519 | 25200 | 0.0016 | - | |
|
| 0.4528 | 25250 | 0.0 | - | |
|
| 0.4537 | 25300 | 0.0 | - | |
|
| 0.4546 | 25350 | 0.0 | - | |
|
| 0.4555 | 25400 | 0.0 | - | |
|
| 0.4564 | 25450 | 0.0 | - | |
|
| 0.4573 | 25500 | 0.0 | - | |
|
| 0.4582 | 25550 | 0.0 | - | |
|
| 0.4591 | 25600 | 0.0 | - | |
|
| 0.4600 | 25650 | 0.0171 | - | |
|
| 0.4609 | 25700 | 0.0 | - | |
|
| 0.4618 | 25750 | 0.0 | - | |
|
| 0.4627 | 25800 | 0.0161 | - | |
|
| 0.4636 | 25850 | 0.0 | - | |
|
| 0.4645 | 25900 | 0.0 | - | |
|
| 0.4654 | 25950 | 0.0 | - | |
|
| 0.4663 | 26000 | 0.0 | - | |
|
| 0.4672 | 26050 | 0.0078 | - | |
|
| 0.4681 | 26100 | 0.0 | - | |
|
| 0.4690 | 26150 | 0.0 | - | |
|
| 0.4699 | 26200 | 0.0 | - | |
|
| 0.4708 | 26250 | 0.0 | - | |
|
| 0.4717 | 26300 | 0.0 | - | |
|
| 0.4726 | 26350 | 0.0 | - | |
|
| 0.4734 | 26400 | 0.0 | - | |
|
| 0.4743 | 26450 | 0.0 | - | |
|
| 0.4752 | 26500 | 0.0091 | - | |
|
| 0.4761 | 26550 | 0.0 | - | |
|
| 0.4770 | 26600 | 0.0 | - | |
|
| 0.4779 | 26650 | 0.0 | - | |
|
| 0.4788 | 26700 | 0.0 | - | |
|
| 0.4797 | 26750 | 0.0 | - | |
|
| 0.4806 | 26800 | 0.0 | - | |
|
| 0.4815 | 26850 | 0.0 | - | |
|
| 0.4824 | 26900 | 0.0 | - | |
|
| 0.4833 | 26950 | 0.0 | - | |
|
| 0.4842 | 27000 | 0.0 | - | |
|
| 0.4851 | 27050 | 0.0 | - | |
|
| 0.4860 | 27100 | 0.0 | - | |
|
| 0.4869 | 27150 | 0.0 | - | |
|
| 0.4878 | 27200 | 0.0 | - | |
|
| 0.4887 | 27250 | 0.0 | - | |
|
| 0.4896 | 27300 | 0.0 | - | |
|
| 0.4905 | 27350 | 0.0 | - | |
|
| 0.4914 | 27400 | 0.0 | - | |
|
| 0.4923 | 27450 | 0.0 | - | |
|
| 0.4932 | 27500 | 0.0 | - | |
|
| 0.4941 | 27550 | 0.0 | - | |
|
| 0.4950 | 27600 | 0.0 | - | |
|
| 0.4959 | 27650 | 0.0 | - | |
|
| 0.4968 | 27700 | 0.0 | - | |
|
| 0.4977 | 27750 | 0.0 | - | |
|
| 0.4986 | 27800 | 0.0 | - | |
|
| 0.4995 | 27850 | 0.0 | - | |
|
| 0.5003 | 27900 | 0.0273 | - | |
|
| 0.5012 | 27950 | 0.0 | - | |
|
| 0.5021 | 28000 | 0.0 | - | |
|
| 0.5030 | 28050 | 0.0 | - | |
|
| 0.5039 | 28100 | 0.0 | - | |
|
| 0.5048 | 28150 | 0.0 | - | |
|
| 0.5057 | 28200 | 0.0 | - | |
|
| 0.5066 | 28250 | 0.0 | - | |
|
| 0.5075 | 28300 | 0.0 | - | |
|
| 0.5084 | 28350 | 0.0 | - | |
|
| 0.5093 | 28400 | 0.0 | - | |
|
| 0.5102 | 28450 | 0.0 | - | |
|
| 0.5111 | 28500 | 0.0 | - | |
|
| 0.5120 | 28550 | 0.0 | - | |
|
| 0.5129 | 28600 | 0.0 | - | |
|
| 0.5138 | 28650 | 0.0 | - | |
|
| 0.5147 | 28700 | 0.0 | - | |
|
| 0.5156 | 28750 | 0.0 | - | |
|
| 0.5165 | 28800 | 0.0 | - | |
|
| 0.5174 | 28850 | 0.0 | - | |
|
| 0.5183 | 28900 | 0.0 | - | |
|
| 0.5192 | 28950 | 0.017 | - | |
|
| 0.5201 | 29000 | 0.0 | - | |
|
| 0.5210 | 29050 | 0.0 | - | |
|
| 0.5219 | 29100 | 0.0 | - | |
|
| 0.5228 | 29150 | 0.0 | - | |
|
| 0.5237 | 29200 | 0.0 | - | |
|
| 0.5246 | 29250 | 0.0 | - | |
|
| 0.5255 | 29300 | 0.0 | - | |
|
| 0.5264 | 29350 | 0.0 | - | |
|
| 0.5273 | 29400 | 0.0 | - | |
|
| 0.5281 | 29450 | 0.0 | - | |
|
| 0.5290 | 29500 | 0.0211 | - | |
|
| 0.5299 | 29550 | 0.0 | - | |
|
| 0.5308 | 29600 | 0.0 | - | |
|
| 0.5317 | 29650 | 0.0 | - | |
|
| 0.5326 | 29700 | 0.0 | - | |
|
| 0.5335 | 29750 | 0.0 | - | |
|
| 0.5344 | 29800 | 0.0 | - | |
|
| 0.5353 | 29850 | 0.0 | - | |
|
| 0.5362 | 29900 | 0.0 | - | |
|
| 0.5371 | 29950 | 0.0 | - | |
|
| 0.5380 | 30000 | 0.0 | - | |
|
| 0.5389 | 30050 | 0.0002 | - | |
|
| 0.5398 | 30100 | 0.0 | - | |
|
| 0.5407 | 30150 | 0.0 | - | |
|
| 0.5416 | 30200 | 0.0 | - | |
|
| 0.5425 | 30250 | 0.0 | - | |
|
| 0.5434 | 30300 | 0.0 | - | |
|
| 0.5443 | 30350 | 0.0 | - | |
|
| 0.5452 | 30400 | 0.0 | - | |
|
| 0.5461 | 30450 | 0.0 | - | |
|
| 0.5470 | 30500 | 0.0158 | - | |
|
| 0.5479 | 30550 | 0.0 | - | |
|
| 0.5488 | 30600 | 0.0 | - | |
|
| 0.5497 | 30650 | 0.0 | - | |
|
| 0.5506 | 30700 | 0.0 | - | |
|
| 0.5515 | 30750 | 0.0165 | - | |
|
| 0.5524 | 30800 | 0.0 | - | |
|
| 0.5533 | 30850 | 0.0 | - | |
|
| 0.5542 | 30900 | 0.0 | - | |
|
| 0.5550 | 30950 | 0.0 | - | |
|
| 0.5559 | 31000 | 0.0 | - | |
|
| 0.5568 | 31050 | 0.0 | - | |
|
| 0.5577 | 31100 | 0.0 | - | |
|
| 0.5586 | 31150 | 0.0132 | - | |
|
| 0.5595 | 31200 | 0.0 | - | |
|
| 0.5604 | 31250 | 0.0 | - | |
|
| 0.5613 | 31300 | 0.0 | - | |
|
| 0.5622 | 31350 | 0.0 | - | |
|
| 0.5631 | 31400 | 0.0 | - | |
|
| 0.5640 | 31450 | 0.0 | - | |
|
| 0.5649 | 31500 | 0.0 | - | |
|
| 0.5658 | 31550 | 0.0 | - | |
|
| 0.5667 | 31600 | 0.0 | - | |
|
| 0.5676 | 31650 | 0.0 | - | |
|
| 0.5685 | 31700 | 0.0 | - | |
|
| 0.5694 | 31750 | 0.0 | - | |
|
| 0.5703 | 31800 | 0.0 | - | |
|
| 0.5712 | 31850 | 0.0 | - | |
|
| 0.5721 | 31900 | 0.0 | - | |
|
| 0.5730 | 31950 | 0.0185 | - | |
|
| 0.5739 | 32000 | 0.0 | - | |
|
| 0.5748 | 32050 | 0.0 | - | |
|
| 0.5757 | 32100 | 0.0 | - | |
|
| 0.5766 | 32150 | 0.0 | - | |
|
| 0.5775 | 32200 | 0.0 | - | |
|
| 0.5784 | 32250 | 0.0 | - | |
|
| 0.5793 | 32300 | 0.0 | - | |
|
| 0.5802 | 32350 | 0.0 | - | |
|
| 0.5811 | 32400 | 0.0 | - | |
|
| 0.5819 | 32450 | 0.0 | - | |
|
| 0.5828 | 32500 | 0.0 | - | |
|
| 0.5837 | 32550 | 0.0 | - | |
|
| 0.5846 | 32600 | 0.0 | - | |
|
| 0.5855 | 32650 | 0.0 | - | |
|
| 0.5864 | 32700 | 0.0 | - | |
|
| 0.5873 | 32750 | 0.0 | - | |
|
| 0.5882 | 32800 | 0.0 | - | |
|
| 0.5891 | 32850 | 0.0 | - | |
|
| 0.5900 | 32900 | 0.0 | - | |
|
| 0.5909 | 32950 | 0.0 | - | |
|
| 0.5918 | 33000 | 0.0 | - | |
|
| 0.5927 | 33050 | 0.0 | - | |
|
| 0.5936 | 33100 | 0.0 | - | |
|
| 0.5945 | 33150 | 0.0 | - | |
|
| 0.5954 | 33200 | 0.0 | - | |
|
| 0.5963 | 33250 | 0.0 | - | |
|
| 0.5972 | 33300 | 0.0 | - | |
|
| 0.5981 | 33350 | 0.0 | - | |
|
| 0.5990 | 33400 | 0.0 | - | |
|
| 0.5999 | 33450 | 0.0 | - | |
|
| 0.6008 | 33500 | 0.0 | - | |
|
| 0.6017 | 33550 | 0.0 | - | |
|
| 0.6026 | 33600 | 0.0 | - | |
|
| 0.6035 | 33650 | 0.0 | - | |
|
| 0.6044 | 33700 | 0.0 | - | |
|
| 0.6053 | 33750 | 0.0 | - | |
|
| 0.6062 | 33800 | 0.0 | - | |
|
| 0.6071 | 33850 | 0.0 | - | |
|
| 0.6080 | 33900 | 0.0 | - | |
|
| 0.6088 | 33950 | 0.0 | - | |
|
| 0.6097 | 34000 | 0.0 | - | |
|
| 0.6106 | 34050 | 0.0 | - | |
|
| 0.6115 | 34100 | 0.0 | - | |
|
| 0.6124 | 34150 | 0.0 | - | |
|
| 0.6133 | 34200 | 0.0 | - | |
|
| 0.6142 | 34250 | 0.0 | - | |
|
| 0.6151 | 34300 | 0.0 | - | |
|
| 0.6160 | 34350 | 0.0 | - | |
|
| 0.6169 | 34400 | 0.0 | - | |
|
| 0.6178 | 34450 | 0.0 | - | |
|
| 0.6187 | 34500 | 0.0 | - | |
|
| 0.6196 | 34550 | 0.0 | - | |
|
| 0.6205 | 34600 | 0.0 | - | |
|
| 0.6214 | 34650 | 0.0 | - | |
|
| 0.6223 | 34700 | 0.0 | - | |
|
| 0.6232 | 34750 | 0.0 | - | |
|
| 0.6241 | 34800 | 0.0 | - | |
|
| 0.6250 | 34850 | 0.0 | - | |
|
| 0.6259 | 34900 | 0.0174 | - | |
|
| 0.6268 | 34950 | 0.0 | - | |
|
| 0.6277 | 35000 | 0.0 | - | |
|
| 0.6286 | 35050 | 0.0 | - | |
|
| 0.6295 | 35100 | 0.0173 | - | |
|
| 0.6304 | 35150 | 0.0 | - | |
|
| 0.6313 | 35200 | 0.0 | - | |
|
| 0.6322 | 35250 | 0.0 | - | |
|
| 0.6331 | 35300 | 0.0 | - | |
|
| 0.6340 | 35350 | 0.0 | - | |
|
| 0.6349 | 35400 | 0.0 | - | |
|
| 0.6357 | 35450 | 0.0 | - | |
|
| 0.6366 | 35500 | 0.0 | - | |
|
| 0.6375 | 35550 | 0.0 | - | |
|
| 0.6384 | 35600 | 0.0 | - | |
|
| 0.6393 | 35650 | 0.0 | - | |
|
| 0.6402 | 35700 | 0.0 | - | |
|
| 0.6411 | 35750 | 0.0 | - | |
|
| 0.6420 | 35800 | 0.0 | - | |
|
| 0.6429 | 35850 | 0.0 | - | |
|
| 0.6438 | 35900 | 0.0 | - | |
|
| 0.6447 | 35950 | 0.0 | - | |
|
| 0.6456 | 36000 | 0.0 | - | |
|
| 0.6465 | 36050 | 0.0 | - | |
|
| 0.6474 | 36100 | 0.0 | - | |
|
| 0.6483 | 36150 | 0.0 | - | |
|
| 0.6492 | 36200 | 0.0 | - | |
|
| 0.6501 | 36250 | 0.0 | - | |
|
| 0.6510 | 36300 | 0.0115 | - | |
|
| 0.6519 | 36350 | 0.0 | - | |
|
| 0.6528 | 36400 | 0.0 | - | |
|
| 0.6537 | 36450 | 0.0 | - | |
|
| 0.6546 | 36500 | 0.0 | - | |
|
| 0.6555 | 36550 | 0.0 | - | |
|
| 0.6564 | 36600 | 0.0204 | - | |
|
| 0.6573 | 36650 | 0.0 | - | |
|
| 0.6582 | 36700 | 0.0125 | - | |
|
| 0.6591 | 36750 | 0.0 | - | |
|
| 0.6600 | 36800 | 0.0 | - | |
|
| 0.6609 | 36850 | 0.0 | - | |
|
| 0.6618 | 36900 | 0.0 | - | |
|
| 0.6626 | 36950 | 0.0 | - | |
|
| 0.6635 | 37000 | 0.0 | - | |
|
| 0.6644 | 37050 | 0.0 | - | |
|
| 0.6653 | 37100 | 0.0109 | - | |
|
| 0.6662 | 37150 | 0.0 | - | |
|
| 0.6671 | 37200 | 0.0 | - | |
|
| 0.6680 | 37250 | 0.0 | - | |
|
| 0.6689 | 37300 | 0.0 | - | |
|
| 0.6698 | 37350 | 0.0 | - | |
|
| 0.6707 | 37400 | 0.0 | - | |
|
| 0.6716 | 37450 | 0.0 | - | |
|
| 0.6725 | 37500 | 0.0 | - | |
|
| 0.6734 | 37550 | 0.0 | - | |
|
| 0.6743 | 37600 | 0.0 | - | |
|
| 0.6752 | 37650 | 0.0 | - | |
|
| 0.6761 | 37700 | 0.0 | - | |
|
| 0.6770 | 37750 | 0.0 | - | |
|
| 0.6779 | 37800 | 0.0 | - | |
|
| 0.6788 | 37850 | 0.0 | - | |
|
| 0.6797 | 37900 | 0.0 | - | |
|
| 0.6806 | 37950 | 0.0 | - | |
|
| 0.6815 | 38000 | 0.0 | - | |
|
| 0.6824 | 38050 | 0.0 | - | |
|
| 0.6833 | 38100 | 0.0 | - | |
|
| 0.6842 | 38150 | 0.0 | - | |
|
| 0.6851 | 38200 | 0.0 | - | |
|
| 0.6860 | 38250 | 0.0 | - | |
|
| 0.6869 | 38300 | 0.0 | - | |
|
| 0.6878 | 38350 | 0.0 | - | |
|
| 0.6887 | 38400 | 0.0 | - | |
|
| 0.6896 | 38450 | 0.0 | - | |
|
| 0.6904 | 38500 | 0.0 | - | |
|
| 0.6913 | 38550 | 0.0 | - | |
|
| 0.6922 | 38600 | 0.0 | - | |
|
| 0.6931 | 38650 | 0.0 | - | |
|
| 0.6940 | 38700 | 0.0 | - | |
|
| 0.6949 | 38750 | 0.0 | - | |
|
| 0.6958 | 38800 | 0.0 | - | |
|
| 0.6967 | 38850 | 0.0 | - | |
|
| 0.6976 | 38900 | 0.0 | - | |
|
| 0.6985 | 38950 | 0.0 | - | |
|
| 0.6994 | 39000 | 0.0 | - | |
|
| 0.7003 | 39050 | 0.0 | - | |
|
| 0.7012 | 39100 | 0.0 | - | |
|
| 0.7021 | 39150 | 0.0 | - | |
|
| 0.7030 | 39200 | 0.0 | - | |
|
| 0.7039 | 39250 | 0.0 | - | |
|
| 0.7048 | 39300 | 0.0 | - | |
|
| 0.7057 | 39350 | 0.0 | - | |
|
| 0.7066 | 39400 | 0.0 | - | |
|
| 0.7075 | 39450 | 0.0 | - | |
|
| 0.7084 | 39500 | 0.0 | - | |
|
| 0.7093 | 39550 | 0.0 | - | |
|
| 0.7102 | 39600 | 0.0 | - | |
|
| 0.7111 | 39650 | 0.0 | - | |
|
| 0.7120 | 39700 | 0.0 | - | |
|
| 0.7129 | 39750 | 0.0 | - | |
|
| 0.7138 | 39800 | 0.0 | - | |
|
| 0.7147 | 39850 | 0.0 | - | |
|
| 0.7156 | 39900 | 0.0 | - | |
|
| 0.7165 | 39950 | 0.0 | - | |
|
| 0.7173 | 40000 | 0.0 | - | |
|
| 0.7182 | 40050 | 0.0 | - | |
|
| 0.7191 | 40100 | 0.0 | - | |
|
| 0.7200 | 40150 | 0.0 | - | |
|
| 0.7209 | 40200 | 0.0 | - | |
|
| 0.7218 | 40250 | 0.0 | - | |
|
| 0.7227 | 40300 | 0.0 | - | |
|
| 0.7236 | 40350 | 0.0 | - | |
|
| 0.7245 | 40400 | 0.0 | - | |
|
| 0.7254 | 40450 | 0.0 | - | |
|
| 0.7263 | 40500 | 0.0 | - | |
|
| 0.7272 | 40550 | 0.0 | - | |
|
| 0.7281 | 40600 | 0.0 | - | |
|
| 0.7290 | 40650 | 0.0 | - | |
|
| 0.7299 | 40700 | 0.0 | - | |
|
| 0.7308 | 40750 | 0.0 | - | |
|
| 0.7317 | 40800 | 0.0 | - | |
|
| 0.7326 | 40850 | 0.0 | - | |
|
| 0.7335 | 40900 | 0.0 | - | |
|
| 0.7344 | 40950 | 0.0 | - | |
|
| 0.7353 | 41000 | 0.0 | - | |
|
| 0.7362 | 41050 | 0.0 | - | |
|
| 0.7371 | 41100 | 0.0 | - | |
|
| 0.7380 | 41150 | 0.0153 | - | |
|
| 0.7389 | 41200 | 0.0 | - | |
|
| 0.7398 | 41250 | 0.0 | - | |
|
| 0.7407 | 41300 | 0.0 | - | |
|
| 0.7416 | 41350 | 0.0 | - | |
|
| 0.7425 | 41400 | 0.0 | - | |
|
| 0.7434 | 41450 | 0.0 | - | |
|
| 0.7442 | 41500 | 0.0 | - | |
|
| 0.7451 | 41550 | 0.0 | - | |
|
| 0.7460 | 41600 | 0.0 | - | |
|
| 0.7469 | 41650 | 0.0 | - | |
|
| 0.7478 | 41700 | 0.0 | - | |
|
| 0.7487 | 41750 | 0.0001 | - | |
|
| 0.7496 | 41800 | 0.0 | - | |
|
| 0.7505 | 41850 | 0.0 | - | |
|
| 0.7514 | 41900 | 0.0 | - | |
|
| 0.7523 | 41950 | 0.0 | - | |
|
| 0.7532 | 42000 | 0.0 | - | |
|
| 0.7541 | 42050 | 0.0 | - | |
|
| 0.7550 | 42100 | 0.0155 | - | |
|
| 0.7559 | 42150 | 0.0231 | - | |
|
| 0.7568 | 42200 | 0.0 | - | |
|
| 0.7577 | 42250 | 0.0 | - | |
|
| 0.7586 | 42300 | 0.0 | - | |
|
| 0.7595 | 42350 | 0.0172 | - | |
|
| 0.7604 | 42400 | 0.0169 | - | |
|
| 0.7613 | 42450 | 0.0 | - | |
|
| 0.7622 | 42500 | 0.0 | - | |
|
| 0.7631 | 42550 | 0.0157 | - | |
|
| 0.7640 | 42600 | 0.0 | - | |
|
| 0.7649 | 42650 | 0.0 | - | |
|
| 0.7658 | 42700 | 0.0 | - | |
|
| 0.7667 | 42750 | 0.0 | - | |
|
| 0.7676 | 42800 | 0.0 | - | |
|
| 0.7685 | 42850 | 0.0 | - | |
|
| 0.7694 | 42900 | 0.0 | - | |
|
| 0.7703 | 42950 | 0.0208 | - | |
|
| 0.7711 | 43000 | 0.0 | - | |
|
| 0.7720 | 43050 | 0.0 | - | |
|
| 0.7729 | 43100 | 0.0 | - | |
|
| 0.7738 | 43150 | 0.0 | - | |
|
| 0.7747 | 43200 | 0.0 | - | |
|
| 0.7756 | 43250 | 0.0 | - | |
|
| 0.7765 | 43300 | 0.0 | - | |
|
| 0.7774 | 43350 | 0.0 | - | |
|
| 0.7783 | 43400 | 0.0 | - | |
|
| 0.7792 | 43450 | 0.0 | - | |
|
| 0.7801 | 43500 | 0.0 | - | |
|
| 0.7810 | 43550 | 0.0 | - | |
|
| 0.7819 | 43600 | 0.0 | - | |
|
| 0.7828 | 43650 | 0.0 | - | |
|
| 0.7837 | 43700 | 0.0 | - | |
|
| 0.7846 | 43750 | 0.0 | - | |
|
| 0.7855 | 43800 | 0.0 | - | |
|
| 0.7864 | 43850 | 0.0 | - | |
|
| 0.7873 | 43900 | 0.0 | - | |
|
| 0.7882 | 43950 | 0.0 | - | |
|
| 0.7891 | 44000 | 0.0 | - | |
|
| 0.7900 | 44050 | 0.0 | - | |
|
| 0.7909 | 44100 | 0.0 | - | |
|
| 0.7918 | 44150 | 0.0 | - | |
|
| 0.7927 | 44200 | 0.0 | - | |
|
| 0.7936 | 44250 | 0.0 | - | |
|
| 0.7945 | 44300 | 0.0 | - | |
|
| 0.7954 | 44350 | 0.0 | - | |
|
| 0.7963 | 44400 | 0.0 | - | |
|
| 0.7972 | 44450 | 0.0 | - | |
|
| 0.7980 | 44500 | 0.0 | - | |
|
| 0.7989 | 44550 | 0.0 | - | |
|
| 0.7998 | 44600 | 0.0 | - | |
|
| 0.8007 | 44650 | 0.0 | - | |
|
| 0.8016 | 44700 | 0.0 | - | |
|
| 0.8025 | 44750 | 0.0 | - | |
|
| 0.8034 | 44800 | 0.0 | - | |
|
| 0.8043 | 44850 | 0.0 | - | |
|
| 0.8052 | 44900 | 0.0 | - | |
|
| 0.8061 | 44950 | 0.0108 | - | |
|
| 0.8070 | 45000 | 0.0 | - | |
|
| 0.8079 | 45050 | 0.0 | - | |
|
| 0.8088 | 45100 | 0.0 | - | |
|
| 0.8097 | 45150 | 0.0 | - | |
|
| 0.8106 | 45200 | 0.0 | - | |
|
| 0.8115 | 45250 | 0.0 | - | |
|
| 0.8124 | 45300 | 0.0 | - | |
|
| 0.8133 | 45350 | 0.0 | - | |
|
| 0.8142 | 45400 | 0.0 | - | |
|
| 0.8151 | 45450 | 0.0 | - | |
|
| 0.8160 | 45500 | 0.0 | - | |
|
| 0.8169 | 45550 | 0.0 | - | |
|
| 0.8178 | 45600 | 0.0 | - | |
|
| 0.8187 | 45650 | 0.0 | - | |
|
| 0.8196 | 45700 | 0.0 | - | |
|
| 0.8205 | 45750 | 0.0 | - | |
|
| 0.8214 | 45800 | 0.0 | - | |
|
| 0.8223 | 45850 | 0.0 | - | |
|
| 0.8232 | 45900 | 0.0 | - | |
|
| 0.8241 | 45950 | 0.0 | - | |
|
| 0.8249 | 46000 | 0.0 | - | |
|
| 0.8258 | 46050 | 0.0 | - | |
|
| 0.8267 | 46100 | 0.0211 | - | |
|
| 0.8276 | 46150 | 0.0 | - | |
|
| 0.8285 | 46200 | 0.0 | - | |
|
| 0.8294 | 46250 | 0.0 | - | |
|
| 0.8303 | 46300 | 0.0 | - | |
|
| 0.8312 | 46350 | 0.0 | - | |
|
| 0.8321 | 46400 | 0.0 | - | |
|
| 0.8330 | 46450 | 0.0 | - | |
|
| 0.8339 | 46500 | 0.0 | - | |
|
| 0.8348 | 46550 | 0.0 | - | |
|
| 0.8357 | 46600 | 0.0 | - | |
|
| 0.8366 | 46650 | 0.0114 | - | |
|
| 0.8375 | 46700 | 0.0 | - | |
|
| 0.8384 | 46750 | 0.0 | - | |
|
| 0.8393 | 46800 | 0.0 | - | |
|
| 0.8402 | 46850 | 0.0 | - | |
|
| 0.8411 | 46900 | 0.0 | - | |
|
| 0.8420 | 46950 | 0.0 | - | |
|
| 0.8429 | 47000 | 0.0 | - | |
|
| 0.8438 | 47050 | 0.0 | - | |
|
| 0.8447 | 47100 | 0.0 | - | |
|
| 0.8456 | 47150 | 0.0 | - | |
|
| 0.8465 | 47200 | 0.0 | - | |
|
| 0.8474 | 47250 | 0.0 | - | |
|
| 0.8483 | 47300 | 0.0 | - | |
|
| 0.8492 | 47350 | 0.0 | - | |
|
| 0.8501 | 47400 | 0.0 | - | |
|
| 0.8510 | 47450 | 0.0 | - | |
|
| 0.8518 | 47500 | 0.0 | - | |
|
| 0.8527 | 47550 | 0.0 | - | |
|
| 0.8536 | 47600 | 0.0 | - | |
|
| 0.8545 | 47650 | 0.0 | - | |
|
| 0.8554 | 47700 | 0.0 | - | |
|
| 0.8563 | 47750 | 0.0 | - | |
|
| 0.8572 | 47800 | 0.0 | - | |
|
| 0.8581 | 47850 | 0.0 | - | |
|
| 0.8590 | 47900 | 0.0 | - | |
|
| 0.8599 | 47950 | 0.0 | - | |
|
| 0.8608 | 48000 | 0.0178 | - | |
|
| 0.8617 | 48050 | 0.0 | - | |
|
| 0.8626 | 48100 | 0.0 | - | |
|
| 0.8635 | 48150 | 0.0 | - | |
|
| 0.8644 | 48200 | 0.0 | - | |
|
| 0.8653 | 48250 | 0.0 | - | |
|
| 0.8662 | 48300 | 0.0 | - | |
|
| 0.8671 | 48350 | 0.0 | - | |
|
| 0.8680 | 48400 | 0.0146 | - | |
|
| 0.8689 | 48450 | 0.0 | - | |
|
| 0.8698 | 48500 | 0.0 | - | |
|
| 0.8707 | 48550 | 0.0 | - | |
|
| 0.8716 | 48600 | 0.0 | - | |
|
| 0.8725 | 48650 | 0.0 | - | |
|
| 0.8734 | 48700 | 0.0 | - | |
|
| 0.8743 | 48750 | 0.0 | - | |
|
| 0.8752 | 48800 | 0.0 | - | |
|
| 0.8761 | 48850 | 0.0146 | - | |
|
| 0.8770 | 48900 | 0.0 | - | |
|
| 0.8779 | 48950 | 0.0 | - | |
|
| 0.8788 | 49000 | 0.0 | - | |
|
| 0.8796 | 49050 | 0.0145 | - | |
|
| 0.8805 | 49100 | 0.0 | - | |
|
| 0.8814 | 49150 | 0.0 | - | |
|
| 0.8823 | 49200 | 0.0 | - | |
|
| 0.8832 | 49250 | 0.0 | - | |
|
| 0.8841 | 49300 | 0.0 | - | |
|
| 0.8850 | 49350 | 0.0 | - | |
|
| 0.8859 | 49400 | 0.0 | - | |
|
| 0.8868 | 49450 | 0.0 | - | |
|
| 0.8877 | 49500 | 0.0 | - | |
|
| 0.8886 | 49550 | 0.0 | - | |
|
| 0.8895 | 49600 | 0.0 | - | |
|
| 0.8904 | 49650 | 0.0 | - | |
|
| 0.8913 | 49700 | 0.0 | - | |
|
| 0.8922 | 49750 | 0.0 | - | |
|
| 0.8931 | 49800 | 0.0 | - | |
|
| 0.8940 | 49850 | 0.0 | - | |
|
| 0.8949 | 49900 | 0.0 | - | |
|
| 0.8958 | 49950 | 0.0 | - | |
|
| 0.8967 | 50000 | 0.0 | - | |
|
| 0.8976 | 50050 | 0.0 | - | |
|
| 0.8985 | 50100 | 0.0 | - | |
|
| 0.8994 | 50150 | 0.0 | - | |
|
| 0.9003 | 50200 | 0.0 | - | |
|
| 0.9012 | 50250 | 0.0 | - | |
|
| 0.9021 | 50300 | 0.0 | - | |
|
| 0.9030 | 50350 | 0.0 | - | |
|
| 0.9039 | 50400 | 0.0 | - | |
|
| 0.9048 | 50450 | 0.0 | - | |
|
| 0.9057 | 50500 | 0.0 | - | |
|
| 0.9065 | 50550 | 0.0 | - | |
|
| 0.9074 | 50600 | 0.0 | - | |
|
| 0.9083 | 50650 | 0.0 | - | |
|
| 0.9092 | 50700 | 0.0 | - | |
|
| 0.9101 | 50750 | 0.0 | - | |
|
| 0.9110 | 50800 | 0.0 | - | |
|
| 0.9119 | 50850 | 0.0 | - | |
|
| 0.9128 | 50900 | 0.0 | - | |
|
| 0.9137 | 50950 | 0.0 | - | |
|
| 0.9146 | 51000 | 0.0 | - | |
|
| 0.9155 | 51050 | 0.0163 | - | |
|
| 0.9164 | 51100 | 0.0 | - | |
|
| 0.9173 | 51150 | 0.0 | - | |
|
| 0.9182 | 51200 | 0.0 | - | |
|
| 0.9191 | 51250 | 0.0 | - | |
|
| 0.9200 | 51300 | 0.0 | - | |
|
| 0.9209 | 51350 | 0.0 | - | |
|
| 0.9218 | 51400 | 0.0 | - | |
|
| 0.9227 | 51450 | 0.0 | - | |
|
| 0.9236 | 51500 | 0.0 | - | |
|
| 0.9245 | 51550 | 0.0 | - | |
|
| 0.9254 | 51600 | 0.0 | - | |
|
| 0.9263 | 51650 | 0.0 | - | |
|
| 0.9272 | 51700 | 0.0 | - | |
|
| 0.9281 | 51750 | 0.0 | - | |
|
| 0.9290 | 51800 | 0.0 | - | |
|
| 0.9299 | 51850 | 0.0 | - | |
|
| 0.9308 | 51900 | 0.0 | - | |
|
| 0.9317 | 51950 | 0.0 | - | |
|
| 0.9326 | 52000 | 0.0 | - | |
|
| 0.9334 | 52050 | 0.0163 | - | |
|
| 0.9343 | 52100 | 0.0 | - | |
|
| 0.9352 | 52150 | 0.0 | - | |
|
| 0.9361 | 52200 | 0.0 | - | |
|
| 0.9370 | 52250 | 0.0 | - | |
|
| 0.9379 | 52300 | 0.0 | - | |
|
| 0.9388 | 52350 | 0.0 | - | |
|
| 0.9397 | 52400 | 0.0 | - | |
|
| 0.9406 | 52450 | 0.0 | - | |
|
| 0.9415 | 52500 | 0.0162 | - | |
|
| 0.9424 | 52550 | 0.0 | - | |
|
| 0.9433 | 52600 | 0.0 | - | |
|
| 0.9442 | 52650 | 0.0 | - | |
|
| 0.9451 | 52700 | 0.0 | - | |
|
| 0.9460 | 52750 | 0.0 | - | |
|
| 0.9469 | 52800 | 0.0 | - | |
|
| 0.9478 | 52850 | 0.0149 | - | |
|
| 0.9487 | 52900 | 0.0 | - | |
|
| 0.9496 | 52950 | 0.0 | - | |
|
| 0.9505 | 53000 | 0.0 | - | |
|
| 0.9514 | 53050 | 0.0 | - | |
|
| 0.9523 | 53100 | 0.0 | - | |
|
| 0.9532 | 53150 | 0.0 | - | |
|
| 0.9541 | 53200 | 0.0 | - | |
|
| 0.9550 | 53250 | 0.0 | - | |
|
| 0.9559 | 53300 | 0.0 | - | |
|
| 0.9568 | 53350 | 0.0 | - | |
|
| 0.9577 | 53400 | 0.0 | - | |
|
| 0.9586 | 53450 | 0.0 | - | |
|
| 0.9595 | 53500 | 0.0 | - | |
|
| 0.9603 | 53550 | 0.0 | - | |
|
| 0.9612 | 53600 | 0.0 | - | |
|
| 0.9621 | 53650 | 0.0 | - | |
|
| 0.9630 | 53700 | 0.0 | - | |
|
| 0.9639 | 53750 | 0.0 | - | |
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| 0.9648 | 53800 | 0.0 | - | |
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| 0.9657 | 53850 | 0.0 | - | |
|
| 0.9666 | 53900 | 0.0 | - | |
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| 0.9675 | 53950 | 0.0 | - | |
|
| 0.9684 | 54000 | 0.0 | - | |
|
| 0.9693 | 54050 | 0.0 | - | |
|
| 0.9702 | 54100 | 0.0 | - | |
|
| 0.9711 | 54150 | 0.0 | - | |
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| 0.9720 | 54200 | 0.0 | - | |
|
| 0.9729 | 54250 | 0.0 | - | |
|
| 0.9738 | 54300 | 0.0 | - | |
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| 0.9747 | 54350 | 0.0 | - | |
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| 0.9756 | 54400 | 0.0 | - | |
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| 0.9765 | 54450 | 0.0 | - | |
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| 0.9774 | 54500 | 0.0 | - | |
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| 0.9783 | 54550 | 0.0 | - | |
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| 0.9792 | 54600 | 0.0 | - | |
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| 0.9801 | 54650 | 0.0 | - | |
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| 0.9810 | 54700 | 0.0 | - | |
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| 0.9819 | 54750 | 0.0 | - | |
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| 0.9828 | 54800 | 0.0 | - | |
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| 0.9837 | 54850 | 0.0 | - | |
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| 0.9846 | 54900 | 0.0 | - | |
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| 0.9855 | 54950 | 0.0 | - | |
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| 0.9864 | 55000 | 0.0 | - | |
|
| 0.9872 | 55050 | 0.0 | - | |
|
| 0.9881 | 55100 | 0.0156 | - | |
|
| 0.9890 | 55150 | 0.0 | - | |
|
| 0.9899 | 55200 | 0.0 | - | |
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| 0.9908 | 55250 | 0.0 | - | |
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| 0.9917 | 55300 | 0.0 | - | |
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| 0.9926 | 55350 | 0.0 | - | |
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| 0.9935 | 55400 | 0.0 | - | |
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| 0.9944 | 55450 | 0.0 | - | |
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| 0.9953 | 55500 | 0.0 | - | |
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| 0.9962 | 55550 | 0.0 | - | |
|
| 0.9971 | 55600 | 0.0 | - | |
|
| 0.9980 | 55650 | 0.0 | - | |
|
| 0.9989 | 55700 | 0.0 | - | |
|
| 0.9998 | 55750 | 0.0 | - | |
|
|
|
### Framework Versions |
|
- Python: 3.10.12 |
|
- SetFit: 1.0.3 |
|
- Sentence Transformers: 2.7.0 |
|
- spaCy: 3.7.4 |
|
- Transformers: 4.40.1 |
|
- PyTorch: 2.2.1+cu121 |
|
- Datasets: 2.19.0 |
|
- Tokenizers: 0.19.1 |
|
|
|
## Citation |
|
|
|
### BibTeX |
|
```bibtex |
|
@article{https://doi.org/10.48550/arxiv.2209.11055, |
|
doi = {10.48550/ARXIV.2209.11055}, |
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url = {https://arxiv.org/abs/2209.11055}, |
|
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, |
|
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, |
|
title = {Efficient Few-Shot Learning Without Prompts}, |
|
publisher = {arXiv}, |
|
year = {2022}, |
|
copyright = {Creative Commons Attribution 4.0 International} |
|
} |
|
``` |
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