|
--- |
|
base_model: sentence-transformers/all-MiniLM-L6-v2 |
|
library_name: setfit |
|
metrics: |
|
- accuracy |
|
pipeline_tag: text-classification |
|
tags: |
|
- setfit |
|
- sentence-transformers |
|
- text-classification |
|
- generated_from_setfit_trainer |
|
widget: |
|
- text: A plus tard |
|
- text: what are microlearning modules |
|
- text: what are the advantages of e-learning over traditional learning |
|
- text: Salut |
|
- text: The user experience could be improved. |
|
inference: true |
|
model-index: |
|
- name: SetFit with sentence-transformers/all-MiniLM-L6-v2 |
|
results: |
|
- task: |
|
type: text-classification |
|
name: Text Classification |
|
dataset: |
|
name: Unknown |
|
type: unknown |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 0.8571428571428571 |
|
name: Accuracy |
|
--- |
|
|
|
# SetFit with sentence-transformers/all-MiniLM-L6-v2 |
|
|
|
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. 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. |
|
|
|
The model has been trained using an efficient few-shot learning technique that involves: |
|
|
|
1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. |
|
2. Training a classification head with features from the fine-tuned Sentence Transformer. |
|
|
|
## Model Details |
|
|
|
### Model Description |
|
- **Model Type:** SetFit |
|
- **Sentence Transformer body:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) |
|
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance |
|
- **Maximum Sequence Length:** 256 tokens |
|
- **Number of Classes:** 7 classes |
|
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) --> |
|
<!-- - **Language:** Unknown --> |
|
<!-- - **License:** Unknown --> |
|
|
|
### Model Sources |
|
|
|
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) |
|
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) |
|
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) |
|
|
|
### Model Labels |
|
| Label | Examples | |
|
|:--------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
|
| recommendations | <ul><li>'how do I find trending courses'</li><li>'what are some popular courses right now'</li><li>'what courses are good for remote working skills'</li></ul> | |
|
| feedback | <ul><li>"I didn't find the answers I was looking for."</li><li>'I find the website confusing to navigate.'</li><li>'The chatbot gave incorrect information.'</li></ul> | |
|
| website-information | <ul><li>'how can I access my bookmarks'</li><li>'how do I edit my profile'</li><li>'where can I find notifications'</li></ul> | |
|
| general-questions | <ul><li>'can you explain the concept of cloud computing'</li><li>'what is the role of peer reviews in online courses'</li><li>'can you explain the difference between synchronous and asynchronous learning'</li></ul> | |
|
| greet-good_bye | <ul><li>'exit'</li><li>'au revoir'</li><li>'sortir'</li></ul> | |
|
| greet-who_are_you | <ul><li>'help please'</li><li>'how can you help me'</li><li>'qui êtes-vous'</li></ul> | |
|
| greet-hi | <ul><li>'Hello buddy'</li><li>'Hi'</li><li>'Salut mon ami'</li></ul> | |
|
|
|
## Evaluation |
|
|
|
### Metrics |
|
| Label | Accuracy | |
|
|:--------|:---------| |
|
| **all** | 0.8571 | |
|
|
|
## Uses |
|
|
|
### Direct Use for Inference |
|
|
|
First install the SetFit library: |
|
|
|
```bash |
|
pip install setfit |
|
``` |
|
|
|
Then you can load this model and run inference. |
|
|
|
```python |
|
from setfit import SetFitModel |
|
|
|
# Download from the 🤗 Hub |
|
model = SetFitModel.from_pretrained("HussienAhmad/SFT_GradProject") |
|
# Run inference |
|
preds = model("Salut") |
|
``` |
|
|
|
<!-- |
|
### Downstream Use |
|
|
|
*List how someone could finetune this model on their own dataset.* |
|
--> |
|
|
|
<!-- |
|
### Out-of-Scope Use |
|
|
|
*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
|
--> |
|
|
|
<!-- |
|
## 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 Set Metrics |
|
| Training set | Min | Median | Max | |
|
|:-------------|:----|:-------|:----| |
|
| Word count | 1 | 6.1880 | 11 | |
|
|
|
| Label | Training Sample Count | |
|
|:--------------------|:----------------------| |
|
| greet-hi | 5 | |
|
| greet-who_are_you | 7 | |
|
| greet-good_bye | 5 | |
|
| general-questions | 28 | |
|
| recommendations | 27 | |
|
| website-information | 28 | |
|
| feedback | 17 | |
|
|
|
### Training Hyperparameters |
|
- batch_size: (4, 4) |
|
- num_epochs: (4, 4) |
|
- max_steps: -1 |
|
- sampling_strategy: oversampling |
|
- body_learning_rate: (2e-05, 1e-05) |
|
- head_learning_rate: 0.01 |
|
- loss: CosineSimilarityLoss |
|
- distance_metric: cosine_distance |
|
- margin: 0.25 |
|
- end_to_end: False |
|
- use_amp: False |
|
- warmup_proportion: 0.1 |
|
- seed: 42 |
|
- eval_max_steps: -1 |
|
- load_best_model_at_end: True |
|
|
|
### Training Results |
|
| Epoch | Step | Training Loss | Validation Loss | |
|
|:-------:|:--------:|:-------------:|:---------------:| |
|
| 0.0004 | 1 | 0.1894 | - | |
|
| 0.0036 | 10 | 0.1796 | - | |
|
| 0.0073 | 20 | 0.4046 | - | |
|
| 0.0109 | 30 | 0.3719 | - | |
|
| 0.0145 | 40 | 0.3065 | - | |
|
| 0.0182 | 50 | 0.1893 | - | |
|
| 0.0218 | 60 | 0.3118 | - | |
|
| 0.0254 | 70 | 0.2084 | - | |
|
| 0.0291 | 80 | 0.3561 | - | |
|
| 0.0327 | 90 | 0.1808 | - | |
|
| 0.0364 | 100 | 0.2126 | - | |
|
| 0.0400 | 110 | 0.2121 | - | |
|
| 0.0436 | 120 | 0.283 | - | |
|
| 0.0473 | 130 | 0.1004 | - | |
|
| 0.0509 | 140 | 0.2684 | - | |
|
| 0.0545 | 150 | 0.139 | - | |
|
| 0.0582 | 160 | 0.2701 | - | |
|
| 0.0618 | 170 | 0.2238 | - | |
|
| 0.0654 | 180 | 0.1276 | - | |
|
| 0.0691 | 190 | 0.053 | - | |
|
| 0.0727 | 200 | 0.2071 | - | |
|
| 0.0763 | 210 | 0.2131 | - | |
|
| 0.0800 | 220 | 0.1646 | - | |
|
| 0.0836 | 230 | 0.1556 | - | |
|
| 0.0872 | 240 | 0.1267 | - | |
|
| 0.0909 | 250 | 0.1275 | - | |
|
| 0.0945 | 260 | 0.2127 | - | |
|
| 0.0981 | 270 | 0.0745 | - | |
|
| 0.1018 | 280 | 0.0274 | - | |
|
| 0.1054 | 290 | 0.2631 | - | |
|
| 0.1091 | 300 | 0.1351 | - | |
|
| 0.1127 | 310 | 0.0402 | - | |
|
| 0.1163 | 320 | 0.1021 | - | |
|
| 0.1200 | 330 | 0.2999 | - | |
|
| 0.1236 | 340 | 0.0935 | - | |
|
| 0.1272 | 350 | 0.1313 | - | |
|
| 0.1309 | 360 | 0.0868 | - | |
|
| 0.1345 | 370 | 0.144 | - | |
|
| 0.1381 | 380 | 0.0756 | - | |
|
| 0.1418 | 390 | 0.0617 | - | |
|
| 0.1454 | 400 | 0.0186 | - | |
|
| 0.1490 | 410 | 0.0637 | - | |
|
| 0.1527 | 420 | 0.0411 | - | |
|
| 0.1563 | 430 | 0.0657 | - | |
|
| 0.1599 | 440 | 0.0561 | - | |
|
| 0.1636 | 450 | 0.096 | - | |
|
| 0.1672 | 460 | 0.2337 | - | |
|
| 0.1708 | 470 | 0.0536 | - | |
|
| 0.1745 | 480 | 0.0631 | - | |
|
| 0.1781 | 490 | 0.0348 | - | |
|
| 0.1818 | 500 | 0.0236 | - | |
|
| 0.1854 | 510 | 0.0126 | - | |
|
| 0.1890 | 520 | 0.0236 | - | |
|
| 0.1927 | 530 | 0.0485 | - | |
|
| 0.1963 | 540 | 0.1579 | - | |
|
| 0.1999 | 550 | 0.0015 | - | |
|
| 0.2036 | 560 | 0.0121 | - | |
|
| 0.2072 | 570 | 0.0131 | - | |
|
| 0.2108 | 580 | 0.005 | - | |
|
| 0.2145 | 590 | 0.0083 | - | |
|
| 0.2181 | 600 | 0.0528 | - | |
|
| 0.2217 | 610 | 0.0069 | - | |
|
| 0.2254 | 620 | 0.0953 | - | |
|
| 0.2290 | 630 | 0.006 | - | |
|
| 0.2326 | 640 | 0.0095 | - | |
|
| 0.2363 | 650 | 0.0051 | - | |
|
| 0.2399 | 660 | 0.0048 | - | |
|
| 0.2435 | 670 | 0.019 | - | |
|
| 0.2472 | 680 | 0.0015 | - | |
|
| 0.2508 | 690 | 0.0037 | - | |
|
| 0.2545 | 700 | 0.005 | - | |
|
| 0.2581 | 710 | 0.0064 | - | |
|
| 0.2617 | 720 | 0.0044 | - | |
|
| 0.2654 | 730 | 0.0015 | - | |
|
| 0.2690 | 740 | 0.0024 | - | |
|
| 0.2726 | 750 | 0.0641 | - | |
|
| 0.2763 | 760 | 0.0439 | - | |
|
| 0.2799 | 770 | 0.0026 | - | |
|
| 0.2835 | 780 | 0.0017 | - | |
|
| 0.2872 | 790 | 0.0015 | - | |
|
| 0.2908 | 800 | 0.0206 | - | |
|
| 0.2944 | 810 | 0.04 | - | |
|
| 0.2981 | 820 | 0.0021 | - | |
|
| 0.3017 | 830 | 0.0036 | - | |
|
| 0.3053 | 840 | 0.0022 | - | |
|
| 0.3090 | 850 | 0.0036 | - | |
|
| 0.3126 | 860 | 0.0015 | - | |
|
| 0.3162 | 870 | 0.0008 | - | |
|
| 0.3199 | 880 | 0.0316 | - | |
|
| 0.3235 | 890 | 0.0019 | - | |
|
| 0.3272 | 900 | 0.0036 | - | |
|
| 0.3308 | 910 | 0.003 | - | |
|
| 0.3344 | 920 | 0.0011 | - | |
|
| 0.3381 | 930 | 0.0015 | - | |
|
| 0.3417 | 940 | 0.0026 | - | |
|
| 0.3453 | 950 | 0.0671 | - | |
|
| 0.3490 | 960 | 0.0079 | - | |
|
| 0.3526 | 970 | 0.0036 | - | |
|
| 0.3562 | 980 | 0.002 | - | |
|
| 0.3599 | 990 | 0.0655 | - | |
|
| 0.3635 | 1000 | 0.002 | - | |
|
| 0.3671 | 1010 | 0.001 | - | |
|
| 0.3708 | 1020 | 0.0008 | - | |
|
| 0.3744 | 1030 | 0.0007 | - | |
|
| 0.3780 | 1040 | 0.0012 | - | |
|
| 0.3817 | 1050 | 0.0162 | - | |
|
| 0.3853 | 1060 | 0.0014 | - | |
|
| 0.3889 | 1070 | 0.0007 | - | |
|
| 0.3926 | 1080 | 0.0013 | - | |
|
| 0.3962 | 1090 | 0.0022 | - | |
|
| 0.3999 | 1100 | 0.0114 | - | |
|
| 0.4035 | 1110 | 0.0011 | - | |
|
| 0.4071 | 1120 | 0.0521 | - | |
|
| 0.4108 | 1130 | 0.0015 | - | |
|
| 0.4144 | 1140 | 0.0006 | - | |
|
| 0.4180 | 1150 | 0.0005 | - | |
|
| 0.4217 | 1160 | 0.0015 | - | |
|
| 0.4253 | 1170 | 0.0928 | - | |
|
| 0.4289 | 1180 | 0.0005 | - | |
|
| 0.4326 | 1190 | 0.0011 | - | |
|
| 0.4362 | 1200 | 0.001 | - | |
|
| 0.4398 | 1210 | 0.0007 | - | |
|
| 0.4435 | 1220 | 0.0011 | - | |
|
| 0.4471 | 1230 | 0.0013 | - | |
|
| 0.4507 | 1240 | 0.0016 | - | |
|
| 0.4544 | 1250 | 0.0014 | - | |
|
| 0.4580 | 1260 | 0.0003 | - | |
|
| 0.4617 | 1270 | 0.001 | - | |
|
| 0.4653 | 1280 | 0.0006 | - | |
|
| 0.4689 | 1290 | 0.0002 | - | |
|
| 0.4726 | 1300 | 0.0006 | - | |
|
| 0.4762 | 1310 | 0.0013 | - | |
|
| 0.4798 | 1320 | 0.0013 | - | |
|
| 0.4835 | 1330 | 0.0007 | - | |
|
| 0.4871 | 1340 | 0.102 | - | |
|
| 0.4907 | 1350 | 0.0037 | - | |
|
| 0.4944 | 1360 | 0.0003 | - | |
|
| 0.4980 | 1370 | 0.0525 | - | |
|
| 0.5016 | 1380 | 0.001 | - | |
|
| 0.5053 | 1390 | 0.0003 | - | |
|
| 0.5089 | 1400 | 0.0013 | - | |
|
| 0.5125 | 1410 | 0.0009 | - | |
|
| 0.5162 | 1420 | 0.0664 | - | |
|
| 0.5198 | 1430 | 0.0003 | - | |
|
| 0.5234 | 1440 | 0.0009 | - | |
|
| 0.5271 | 1450 | 0.002 | - | |
|
| 0.5307 | 1460 | 0.0149 | - | |
|
| 0.5344 | 1470 | 0.0004 | - | |
|
| 0.5380 | 1480 | 0.0008 | - | |
|
| 0.5416 | 1490 | 0.0007 | - | |
|
| 0.5453 | 1500 | 0.0006 | - | |
|
| 0.5489 | 1510 | 0.0302 | - | |
|
| 0.5525 | 1520 | 0.0006 | - | |
|
| 0.5562 | 1530 | 0.0008 | - | |
|
| 0.5598 | 1540 | 0.0011 | - | |
|
| 0.5634 | 1550 | 0.0005 | - | |
|
| 0.5671 | 1560 | 0.001 | - | |
|
| 0.5707 | 1570 | 0.0006 | - | |
|
| 0.5743 | 1580 | 0.0008 | - | |
|
| 0.5780 | 1590 | 0.0004 | - | |
|
| 0.5816 | 1600 | 0.0004 | - | |
|
| 0.5852 | 1610 | 0.0006 | - | |
|
| 0.5889 | 1620 | 0.0003 | - | |
|
| 0.5925 | 1630 | 0.0007 | - | |
|
| 0.5961 | 1640 | 0.0003 | - | |
|
| 0.5998 | 1650 | 0.001 | - | |
|
| 0.6034 | 1660 | 0.0006 | - | |
|
| 0.6071 | 1670 | 0.0004 | - | |
|
| 0.6107 | 1680 | 0.0029 | - | |
|
| 0.6143 | 1690 | 0.0016 | - | |
|
| 0.6180 | 1700 | 0.0007 | - | |
|
| 0.6216 | 1710 | 0.0003 | - | |
|
| 0.6252 | 1720 | 0.0006 | - | |
|
| 0.6289 | 1730 | 0.0006 | - | |
|
| 0.6325 | 1740 | 0.0014 | - | |
|
| 0.6361 | 1750 | 0.0019 | - | |
|
| 0.6398 | 1760 | 0.0008 | - | |
|
| 0.6434 | 1770 | 0.0003 | - | |
|
| 0.6470 | 1780 | 0.0002 | - | |
|
| 0.6507 | 1790 | 0.0055 | - | |
|
| 0.6543 | 1800 | 0.0029 | - | |
|
| 0.6579 | 1810 | 0.0017 | - | |
|
| 0.6616 | 1820 | 0.0049 | - | |
|
| 0.6652 | 1830 | 0.0004 | - | |
|
| 0.6688 | 1840 | 0.0013 | - | |
|
| 0.6725 | 1850 | 0.0003 | - | |
|
| 0.6761 | 1860 | 0.0004 | - | |
|
| 0.6798 | 1870 | 0.0014 | - | |
|
| 0.6834 | 1880 | 0.0011 | - | |
|
| 0.6870 | 1890 | 0.0022 | - | |
|
| 0.6907 | 1900 | 0.0025 | - | |
|
| 0.6943 | 1910 | 0.0002 | - | |
|
| 0.6979 | 1920 | 0.0004 | - | |
|
| 0.7016 | 1930 | 0.0002 | - | |
|
| 0.7052 | 1940 | 0.0003 | - | |
|
| 0.7088 | 1950 | 0.0007 | - | |
|
| 0.7125 | 1960 | 0.0003 | - | |
|
| 0.7161 | 1970 | 0.0004 | - | |
|
| 0.7197 | 1980 | 0.0005 | - | |
|
| 0.7234 | 1990 | 0.0002 | - | |
|
| 0.7270 | 2000 | 0.0003 | - | |
|
| 0.7306 | 2010 | 0.0003 | - | |
|
| 0.7343 | 2020 | 0.0004 | - | |
|
| 0.7379 | 2030 | 0.0006 | - | |
|
| 0.7415 | 2040 | 0.0007 | - | |
|
| 0.7452 | 2050 | 0.0009 | - | |
|
| 0.7488 | 2060 | 0.0007 | - | |
|
| 0.7525 | 2070 | 0.0002 | - | |
|
| 0.7561 | 2080 | 0.0002 | - | |
|
| 0.7597 | 2090 | 0.0003 | - | |
|
| 0.7634 | 2100 | 0.0006 | - | |
|
| 0.7670 | 2110 | 0.0003 | - | |
|
| 0.7706 | 2120 | 0.0009 | - | |
|
| 0.7743 | 2130 | 0.0004 | - | |
|
| 0.7779 | 2140 | 0.0003 | - | |
|
| 0.7815 | 2150 | 0.0004 | - | |
|
| 0.7852 | 2160 | 0.0003 | - | |
|
| 0.7888 | 2170 | 0.0003 | - | |
|
| 0.7924 | 2180 | 0.0005 | - | |
|
| 0.7961 | 2190 | 0.0002 | - | |
|
| 0.7997 | 2200 | 0.0003 | - | |
|
| 0.8033 | 2210 | 0.0008 | - | |
|
| 0.8070 | 2220 | 0.0003 | - | |
|
| 0.8106 | 2230 | 0.0001 | - | |
|
| 0.8142 | 2240 | 0.0002 | - | |
|
| 0.8179 | 2250 | 0.0002 | - | |
|
| 0.8215 | 2260 | 0.0002 | - | |
|
| 0.8252 | 2270 | 0.0006 | - | |
|
| 0.8288 | 2280 | 0.0002 | - | |
|
| 0.8324 | 2290 | 0.0004 | - | |
|
| 0.8361 | 2300 | 0.0004 | - | |
|
| 0.8397 | 2310 | 0.0006 | - | |
|
| 0.8433 | 2320 | 0.0002 | - | |
|
| 0.8470 | 2330 | 0.0002 | - | |
|
| 0.8506 | 2340 | 0.0003 | - | |
|
| 0.8542 | 2350 | 0.0002 | - | |
|
| 0.8579 | 2360 | 0.0005 | - | |
|
| 0.8615 | 2370 | 0.0033 | - | |
|
| 0.8651 | 2380 | 0.0009 | - | |
|
| 0.8688 | 2390 | 0.0004 | - | |
|
| 0.8724 | 2400 | 0.0002 | - | |
|
| 0.8760 | 2410 | 0.0003 | - | |
|
| 0.8797 | 2420 | 0.0001 | - | |
|
| 0.8833 | 2430 | 0.0002 | - | |
|
| 0.8870 | 2440 | 0.0007 | - | |
|
| 0.8906 | 2450 | 0.0007 | - | |
|
| 0.8942 | 2460 | 0.0002 | - | |
|
| 0.8979 | 2470 | 0.0002 | - | |
|
| 0.9015 | 2480 | 0.0005 | - | |
|
| 0.9051 | 2490 | 0.0011 | - | |
|
| 0.9088 | 2500 | 0.0002 | - | |
|
| 0.9124 | 2510 | 0.0003 | - | |
|
| 0.9160 | 2520 | 0.0002 | - | |
|
| 0.9197 | 2530 | 0.0007 | - | |
|
| 0.9233 | 2540 | 0.0003 | - | |
|
| 0.9269 | 2550 | 0.0002 | - | |
|
| 0.9306 | 2560 | 0.0001 | - | |
|
| 0.9342 | 2570 | 0.0015 | - | |
|
| 0.9378 | 2580 | 0.0004 | - | |
|
| 0.9415 | 2590 | 0.0004 | - | |
|
| 0.9451 | 2600 | 0.0004 | - | |
|
| 0.9487 | 2610 | 0.0004 | - | |
|
| 0.9524 | 2620 | 0.0007 | - | |
|
| 0.9560 | 2630 | 0.0002 | - | |
|
| 0.9597 | 2640 | 0.0003 | - | |
|
| 0.9633 | 2650 | 0.0002 | - | |
|
| 0.9669 | 2660 | 0.0001 | - | |
|
| 0.9706 | 2670 | 0.0006 | - | |
|
| 0.9742 | 2680 | 0.0005 | - | |
|
| 0.9778 | 2690 | 0.0001 | - | |
|
| 0.9815 | 2700 | 0.0003 | - | |
|
| 0.9851 | 2710 | 0.0002 | - | |
|
| 0.9887 | 2720 | 0.0031 | - | |
|
| 0.9924 | 2730 | 0.0005 | - | |
|
| 0.9960 | 2740 | 0.0003 | - | |
|
| 0.9996 | 2750 | 0.0003 | - | |
|
| **1.0** | **2751** | **-** | **0.0498** | |
|
| 1.0033 | 2760 | 0.0009 | - | |
|
| 1.0069 | 2770 | 0.0001 | - | |
|
| 1.0105 | 2780 | 0.0003 | - | |
|
| 1.0142 | 2790 | 0.0003 | - | |
|
| 1.0178 | 2800 | 0.0004 | - | |
|
| 1.0214 | 2810 | 0.0009 | - | |
|
| 1.0251 | 2820 | 0.0004 | - | |
|
| 1.0287 | 2830 | 0.0004 | - | |
|
| 1.0324 | 2840 | 0.0004 | - | |
|
| 1.0360 | 2850 | 0.0049 | - | |
|
| 1.0396 | 2860 | 0.0003 | - | |
|
| 1.0433 | 2870 | 0.0056 | - | |
|
| 1.0469 | 2880 | 0.0003 | - | |
|
| 1.0505 | 2890 | 0.0002 | - | |
|
| 1.0542 | 2900 | 0.0002 | - | |
|
| 1.0578 | 2910 | 0.0004 | - | |
|
| 1.0614 | 2920 | 0.0002 | - | |
|
| 1.0651 | 2930 | 0.0002 | - | |
|
| 1.0687 | 2940 | 0.0002 | - | |
|
| 1.0723 | 2950 | 0.0001 | - | |
|
| 1.0760 | 2960 | 0.0045 | - | |
|
| 1.0796 | 2970 | 0.0002 | - | |
|
| 1.0832 | 2980 | 0.0003 | - | |
|
| 1.0869 | 2990 | 0.0002 | - | |
|
| 1.0905 | 3000 | 0.0019 | - | |
|
| 1.0941 | 3010 | 0.0001 | - | |
|
| 1.0978 | 3020 | 0.0001 | - | |
|
| 1.1014 | 3030 | 0.0003 | - | |
|
| 1.1051 | 3040 | 0.0007 | - | |
|
| 1.1087 | 3050 | 0.0004 | - | |
|
| 1.1123 | 3060 | 0.0003 | - | |
|
| 1.1160 | 3070 | 0.0006 | - | |
|
| 1.1196 | 3080 | 0.0005 | - | |
|
| 1.1232 | 3090 | 0.0004 | - | |
|
| 1.1269 | 3100 | 0.0003 | - | |
|
| 1.1305 | 3110 | 0.0002 | - | |
|
| 1.1341 | 3120 | 0.0002 | - | |
|
| 1.1378 | 3130 | 0.0003 | - | |
|
| 1.1414 | 3140 | 0.0007 | - | |
|
| 1.1450 | 3150 | 0.0001 | - | |
|
| 1.1487 | 3160 | 0.0011 | - | |
|
| 1.1523 | 3170 | 0.0003 | - | |
|
| 1.1559 | 3180 | 0.0004 | - | |
|
| 1.1596 | 3190 | 0.0001 | - | |
|
| 1.1632 | 3200 | 0.0002 | - | |
|
| 1.1668 | 3210 | 0.0003 | - | |
|
| 1.1705 | 3220 | 0.0003 | - | |
|
| 1.1741 | 3230 | 0.0002 | - | |
|
| 1.1778 | 3240 | 0.0001 | - | |
|
| 1.1814 | 3250 | 0.0013 | - | |
|
| 1.1850 | 3260 | 0.0003 | - | |
|
| 1.1887 | 3270 | 0.0004 | - | |
|
| 1.1923 | 3280 | 0.0002 | - | |
|
| 1.1959 | 3290 | 0.0002 | - | |
|
| 1.1996 | 3300 | 0.0004 | - | |
|
| 1.2032 | 3310 | 0.0002 | - | |
|
| 1.2068 | 3320 | 0.0001 | - | |
|
| 1.2105 | 3330 | 0.0002 | - | |
|
| 1.2141 | 3340 | 0.0006 | - | |
|
| 1.2177 | 3350 | 0.0002 | - | |
|
| 1.2214 | 3360 | 0.0001 | - | |
|
| 1.2250 | 3370 | 0.0004 | - | |
|
| 1.2286 | 3380 | 0.0005 | - | |
|
| 1.2323 | 3390 | 0.0016 | - | |
|
| 1.2359 | 3400 | 0.0001 | - | |
|
| 1.2395 | 3410 | 0.0004 | - | |
|
| 1.2432 | 3420 | 0.0002 | - | |
|
| 1.2468 | 3430 | 0.0002 | - | |
|
| 1.2505 | 3440 | 0.0001 | - | |
|
| 1.2541 | 3450 | 0.0001 | - | |
|
| 1.2577 | 3460 | 0.0003 | - | |
|
| 1.2614 | 3470 | 0.0001 | - | |
|
| 1.2650 | 3480 | 0.001 | - | |
|
| 1.2686 | 3490 | 0.0003 | - | |
|
| 1.2723 | 3500 | 0.0002 | - | |
|
| 1.2759 | 3510 | 0.0001 | - | |
|
| 1.2795 | 3520 | 0.0004 | - | |
|
| 1.2832 | 3530 | 0.0001 | - | |
|
| 1.2868 | 3540 | 0.0001 | - | |
|
| 1.2904 | 3550 | 0.0002 | - | |
|
| 1.2941 | 3560 | 0.0003 | - | |
|
| 1.2977 | 3570 | 0.0014 | - | |
|
| 1.3013 | 3580 | 0.0005 | - | |
|
| 1.3050 | 3590 | 0.0003 | - | |
|
| 1.3086 | 3600 | 0.0002 | - | |
|
| 1.3123 | 3610 | 0.0002 | - | |
|
| 1.3159 | 3620 | 0.0001 | - | |
|
| 1.3195 | 3630 | 0.0002 | - | |
|
| 1.3232 | 3640 | 0.0002 | - | |
|
| 1.3268 | 3650 | 0.0001 | - | |
|
| 1.3304 | 3660 | 0.0246 | - | |
|
| 1.3341 | 3670 | 0.0002 | - | |
|
| 1.3377 | 3680 | 0.0002 | - | |
|
| 1.3413 | 3690 | 0.0005 | - | |
|
| 1.3450 | 3700 | 0.0108 | - | |
|
| 1.3486 | 3710 | 0.0001 | - | |
|
| 1.3522 | 3720 | 0.0003 | - | |
|
| 1.3559 | 3730 | 0.0002 | - | |
|
| 1.3595 | 3740 | 0.0001 | - | |
|
| 1.3631 | 3750 | 0.0001 | - | |
|
| 1.3668 | 3760 | 0.0003 | - | |
|
| 1.3704 | 3770 | 0.0004 | - | |
|
| 1.3740 | 3780 | 0.0001 | - | |
|
| 1.3777 | 3790 | 0.0009 | - | |
|
| 1.3813 | 3800 | 0.0002 | - | |
|
| 1.3850 | 3810 | 0.0002 | - | |
|
| 1.3886 | 3820 | 0.0001 | - | |
|
| 1.3922 | 3830 | 0.0001 | - | |
|
| 1.3959 | 3840 | 0.0003 | - | |
|
| 1.3995 | 3850 | 0.0003 | - | |
|
| 1.4031 | 3860 | 0.0005 | - | |
|
| 1.4068 | 3870 | 0.0002 | - | |
|
| 1.4104 | 3880 | 0.0001 | - | |
|
| 1.4140 | 3890 | 0.0003 | - | |
|
| 1.4177 | 3900 | 0.0001 | - | |
|
| 1.4213 | 3910 | 0.0002 | - | |
|
| 1.4249 | 3920 | 0.0003 | - | |
|
| 1.4286 | 3930 | 0.0002 | - | |
|
| 1.4322 | 3940 | 0.0002 | - | |
|
| 1.4358 | 3950 | 0.0002 | - | |
|
| 1.4395 | 3960 | 0.0001 | - | |
|
| 1.4431 | 3970 | 0.0001 | - | |
|
| 1.4467 | 3980 | 0.0001 | - | |
|
| 1.4504 | 3990 | 0.0002 | - | |
|
| 1.4540 | 4000 | 0.0001 | - | |
|
| 1.4577 | 4010 | 0.001 | - | |
|
| 1.4613 | 4020 | 0.0001 | - | |
|
| 1.4649 | 4030 | 0.0001 | - | |
|
| 1.4686 | 4040 | 0.0005 | - | |
|
| 1.4722 | 4050 | 0.0003 | - | |
|
| 1.4758 | 4060 | 0.0001 | - | |
|
| 1.4795 | 4070 | 0.0002 | - | |
|
| 1.4831 | 4080 | 0.0002 | - | |
|
| 1.4867 | 4090 | 0.001 | - | |
|
| 1.4904 | 4100 | 0.0005 | - | |
|
| 1.4940 | 4110 | 0.0003 | - | |
|
| 1.4976 | 4120 | 0.0004 | - | |
|
| 1.5013 | 4130 | 0.0002 | - | |
|
| 1.5049 | 4140 | 0.0001 | - | |
|
| 1.5085 | 4150 | 0.0012 | - | |
|
| 1.5122 | 4160 | 0.0008 | - | |
|
| 1.5158 | 4170 | 0.0004 | - | |
|
| 1.5194 | 4180 | 0.001 | - | |
|
| 1.5231 | 4190 | 0.0001 | - | |
|
| 1.5267 | 4200 | 0.0005 | - | |
|
| 1.5304 | 4210 | 0.0001 | - | |
|
| 1.5340 | 4220 | 0.0001 | - | |
|
| 1.5376 | 4230 | 0.0002 | - | |
|
| 1.5413 | 4240 | 0.0002 | - | |
|
| 1.5449 | 4250 | 0.0002 | - | |
|
| 1.5485 | 4260 | 0.0002 | - | |
|
| 1.5522 | 4270 | 0.0001 | - | |
|
| 1.5558 | 4280 | 0.0002 | - | |
|
| 1.5594 | 4290 | 0.0001 | - | |
|
| 1.5631 | 4300 | 0.0001 | - | |
|
| 1.5667 | 4310 | 0.0002 | - | |
|
| 1.5703 | 4320 | 0.0001 | - | |
|
| 1.5740 | 4330 | 0.0001 | - | |
|
| 1.5776 | 4340 | 0.0001 | - | |
|
| 1.5812 | 4350 | 0.0001 | - | |
|
| 1.5849 | 4360 | 0.0001 | - | |
|
| 1.5885 | 4370 | 0.0002 | - | |
|
| 1.5921 | 4380 | 0.0001 | - | |
|
| 1.5958 | 4390 | 0.0004 | - | |
|
| 1.5994 | 4400 | 0.0005 | - | |
|
| 1.6031 | 4410 | 0.0003 | - | |
|
| 1.6067 | 4420 | 0.0002 | - | |
|
| 1.6103 | 4430 | 0.0001 | - | |
|
| 1.6140 | 4440 | 0.0002 | - | |
|
| 1.6176 | 4450 | 0.0002 | - | |
|
| 1.6212 | 4460 | 0.0001 | - | |
|
| 1.6249 | 4470 | 0.0003 | - | |
|
| 1.6285 | 4480 | 0.0003 | - | |
|
| 1.6321 | 4490 | 0.0001 | - | |
|
| 1.6358 | 4500 | 0.0001 | - | |
|
| 1.6394 | 4510 | 0.0002 | - | |
|
| 1.6430 | 4520 | 0.0002 | - | |
|
| 1.6467 | 4530 | 0.0003 | - | |
|
| 1.6503 | 4540 | 0.0001 | - | |
|
| 1.6539 | 4550 | 0.0001 | - | |
|
| 1.6576 | 4560 | 0.0002 | - | |
|
| 1.6612 | 4570 | 0.0003 | - | |
|
| 1.6648 | 4580 | 0.0002 | - | |
|
| 1.6685 | 4590 | 0.0002 | - | |
|
| 1.6721 | 4600 | 0.0002 | - | |
|
| 1.6758 | 4610 | 0.0002 | - | |
|
| 1.6794 | 4620 | 0.0002 | - | |
|
| 1.6830 | 4630 | 0.0002 | - | |
|
| 1.6867 | 4640 | 0.0001 | - | |
|
| 1.6903 | 4650 | 0.0001 | - | |
|
| 1.6939 | 4660 | 0.0001 | - | |
|
| 1.6976 | 4670 | 0.0002 | - | |
|
| 1.7012 | 4680 | 0.0001 | - | |
|
| 1.7048 | 4690 | 0.0001 | - | |
|
| 1.7085 | 4700 | 0.0002 | - | |
|
| 1.7121 | 4710 | 0.001 | - | |
|
| 1.7157 | 4720 | 0.0001 | - | |
|
| 1.7194 | 4730 | 0.0002 | - | |
|
| 1.7230 | 4740 | 0.0001 | - | |
|
| 1.7266 | 4750 | 0.0002 | - | |
|
| 1.7303 | 4760 | 0.0001 | - | |
|
| 1.7339 | 4770 | 0.0002 | - | |
|
| 1.7375 | 4780 | 0.0001 | - | |
|
| 1.7412 | 4790 | 0.0001 | - | |
|
| 1.7448 | 4800 | 0.0001 | - | |
|
| 1.7485 | 4810 | 0.0001 | - | |
|
| 1.7521 | 4820 | 0.0002 | - | |
|
| 1.7557 | 4830 | 0.0012 | - | |
|
| 1.7594 | 4840 | 0.0003 | - | |
|
| 1.7630 | 4850 | 0.0008 | - | |
|
| 1.7666 | 4860 | 0.0001 | - | |
|
| 1.7703 | 4870 | 0.0002 | - | |
|
| 1.7739 | 4880 | 0.0001 | - | |
|
| 1.7775 | 4890 | 0.0008 | - | |
|
| 1.7812 | 4900 | 0.0001 | - | |
|
| 1.7848 | 4910 | 0.0001 | - | |
|
| 1.7884 | 4920 | 0.0001 | - | |
|
| 1.7921 | 4930 | 0.0001 | - | |
|
| 1.7957 | 4940 | 0.0006 | - | |
|
| 1.7993 | 4950 | 0.0002 | - | |
|
| 1.8030 | 4960 | 0.0002 | - | |
|
| 1.8066 | 4970 | 0.0004 | - | |
|
| 1.8103 | 4980 | 0.0001 | - | |
|
| 1.8139 | 4990 | 0.0001 | - | |
|
| 1.8175 | 5000 | 0.0004 | - | |
|
| 1.8212 | 5010 | 0.0001 | - | |
|
| 1.8248 | 5020 | 0.0001 | - | |
|
| 1.8284 | 5030 | 0.0003 | - | |
|
| 1.8321 | 5040 | 0.0001 | - | |
|
| 1.8357 | 5050 | 0.0001 | - | |
|
| 1.8393 | 5060 | 0.0001 | - | |
|
| 1.8430 | 5070 | 0.0003 | - | |
|
| 1.8466 | 5080 | 0.0001 | - | |
|
| 1.8502 | 5090 | 0.0001 | - | |
|
| 1.8539 | 5100 | 0.0001 | - | |
|
| 1.8575 | 5110 | 0.0001 | - | |
|
| 1.8611 | 5120 | 0.0002 | - | |
|
| 1.8648 | 5130 | 0.0003 | - | |
|
| 1.8684 | 5140 | 0.0002 | - | |
|
| 1.8720 | 5150 | 0.0001 | - | |
|
| 1.8757 | 5160 | 0.0001 | - | |
|
| 1.8793 | 5170 | 0.0001 | - | |
|
| 1.8830 | 5180 | 0.0002 | - | |
|
| 1.8866 | 5190 | 0.0004 | - | |
|
| 1.8902 | 5200 | 0.0001 | - | |
|
| 1.8939 | 5210 | 0.0001 | - | |
|
| 1.8975 | 5220 | 0.0003 | - | |
|
| 1.9011 | 5230 | 0.0001 | - | |
|
| 1.9048 | 5240 | 0.0002 | - | |
|
| 1.9084 | 5250 | 0.0003 | - | |
|
| 1.9120 | 5260 | 0.0001 | - | |
|
| 1.9157 | 5270 | 0.0002 | - | |
|
| 1.9193 | 5280 | 0.0002 | - | |
|
| 1.9229 | 5290 | 0.0004 | - | |
|
| 1.9266 | 5300 | 0.0001 | - | |
|
| 1.9302 | 5310 | 0.0001 | - | |
|
| 1.9338 | 5320 | 0.0002 | - | |
|
| 1.9375 | 5330 | 0.0002 | - | |
|
| 1.9411 | 5340 | 0.0003 | - | |
|
| 1.9447 | 5350 | 0.0002 | - | |
|
| 1.9484 | 5360 | 0.0001 | - | |
|
| 1.9520 | 5370 | 0.0002 | - | |
|
| 1.9557 | 5380 | 0.0001 | - | |
|
| 1.9593 | 5390 | 0.0002 | - | |
|
| 1.9629 | 5400 | 0.0001 | - | |
|
| 1.9666 | 5410 | 0.0009 | - | |
|
| 1.9702 | 5420 | 0.0001 | - | |
|
| 1.9738 | 5430 | 0.0002 | - | |
|
| 1.9775 | 5440 | 0.0001 | - | |
|
| 1.9811 | 5450 | 0.0001 | - | |
|
| 1.9847 | 5460 | 0.0002 | - | |
|
| 1.9884 | 5470 | 0.0002 | - | |
|
| 1.9920 | 5480 | 0.0002 | - | |
|
| 1.9956 | 5490 | 0.0001 | - | |
|
| 1.9993 | 5500 | 0.0001 | - | |
|
| 2.0 | 5502 | - | 0.0628 | |
|
| 2.0029 | 5510 | 0.0001 | - | |
|
| 2.0065 | 5520 | 0.0004 | - | |
|
| 2.0102 | 5530 | 0.0003 | - | |
|
| 2.0138 | 5540 | 0.0002 | - | |
|
| 2.0174 | 5550 | 0.0002 | - | |
|
| 2.0211 | 5560 | 0.0002 | - | |
|
| 2.0247 | 5570 | 0.0002 | - | |
|
| 2.0284 | 5580 | 0.0003 | - | |
|
| 2.0320 | 5590 | 0.0001 | - | |
|
| 2.0356 | 5600 | 0.0002 | - | |
|
| 2.0393 | 5610 | 0.0001 | - | |
|
| 2.0429 | 5620 | 0.0001 | - | |
|
| 2.0465 | 5630 | 0.001 | - | |
|
| 2.0502 | 5640 | 0.0001 | - | |
|
| 2.0538 | 5650 | 0.0001 | - | |
|
| 2.0574 | 5660 | 0.0003 | - | |
|
| 2.0611 | 5670 | 0.0001 | - | |
|
| 2.0647 | 5680 | 0.0001 | - | |
|
| 2.0683 | 5690 | 0.0002 | - | |
|
| 2.0720 | 5700 | 0.0004 | - | |
|
| 2.0756 | 5710 | 0.0001 | - | |
|
| 2.0792 | 5720 | 0.0001 | - | |
|
| 2.0829 | 5730 | 0.0001 | - | |
|
| 2.0865 | 5740 | 0.0001 | - | |
|
| 2.0901 | 5750 | 0.0019 | - | |
|
| 2.0938 | 5760 | 0.0001 | - | |
|
| 2.0974 | 5770 | 0.0003 | - | |
|
| 2.1011 | 5780 | 0.0002 | - | |
|
| 2.1047 | 5790 | 0.0001 | - | |
|
| 2.1083 | 5800 | 0.0001 | - | |
|
| 2.1120 | 5810 | 0.0001 | - | |
|
| 2.1156 | 5820 | 0.0006 | - | |
|
| 2.1192 | 5830 | 0.0001 | - | |
|
| 2.1229 | 5840 | 0.0001 | - | |
|
| 2.1265 | 5850 | 0.0001 | - | |
|
| 2.1301 | 5860 | 0.0 | - | |
|
| 2.1338 | 5870 | 0.0001 | - | |
|
| 2.1374 | 5880 | 0.0001 | - | |
|
| 2.1410 | 5890 | 0.0001 | - | |
|
| 2.1447 | 5900 | 0.0002 | - | |
|
| 2.1483 | 5910 | 0.0005 | - | |
|
| 2.1519 | 5920 | 0.0001 | - | |
|
| 2.1556 | 5930 | 0.0004 | - | |
|
| 2.1592 | 5940 | 0.0001 | - | |
|
| 2.1628 | 5950 | 0.0001 | - | |
|
| 2.1665 | 5960 | 0.0001 | - | |
|
| 2.1701 | 5970 | 0.0001 | - | |
|
| 2.1738 | 5980 | 0.0001 | - | |
|
| 2.1774 | 5990 | 0.0002 | - | |
|
| 2.1810 | 6000 | 0.0001 | - | |
|
| 2.1847 | 6010 | 0.0001 | - | |
|
| 2.1883 | 6020 | 0.0001 | - | |
|
| 2.1919 | 6030 | 0.0001 | - | |
|
| 2.1956 | 6040 | 0.0001 | - | |
|
| 2.1992 | 6050 | 0.0002 | - | |
|
| 2.2028 | 6060 | 0.0001 | - | |
|
| 2.2065 | 6070 | 0.0001 | - | |
|
| 2.2101 | 6080 | 0.0001 | - | |
|
| 2.2137 | 6090 | 0.0001 | - | |
|
| 2.2174 | 6100 | 0.0001 | - | |
|
| 2.2210 | 6110 | 0.0004 | - | |
|
| 2.2246 | 6120 | 0.0001 | - | |
|
| 2.2283 | 6130 | 0.0001 | - | |
|
| 2.2319 | 6140 | 0.0001 | - | |
|
| 2.2356 | 6150 | 0.0005 | - | |
|
| 2.2392 | 6160 | 0.0 | - | |
|
| 2.2428 | 6170 | 0.0001 | - | |
|
| 2.2465 | 6180 | 0.0001 | - | |
|
| 2.2501 | 6190 | 0.0002 | - | |
|
| 2.2537 | 6200 | 0.0001 | - | |
|
| 2.2574 | 6210 | 0.0001 | - | |
|
| 2.2610 | 6220 | 0.0001 | - | |
|
| 2.2646 | 6230 | 0.0001 | - | |
|
| 2.2683 | 6240 | 0.0006 | - | |
|
| 2.2719 | 6250 | 0.0001 | - | |
|
| 2.2755 | 6260 | 0.0 | - | |
|
| 2.2792 | 6270 | 0.0003 | - | |
|
| 2.2828 | 6280 | 0.0001 | - | |
|
| 2.2864 | 6290 | 0.0002 | - | |
|
| 2.2901 | 6300 | 0.0001 | - | |
|
| 2.2937 | 6310 | 0.0004 | - | |
|
| 2.2973 | 6320 | 0.0001 | - | |
|
| 2.3010 | 6330 | 0.0002 | - | |
|
| 2.3046 | 6340 | 0.0002 | - | |
|
| 2.3083 | 6350 | 0.0004 | - | |
|
| 2.3119 | 6360 | 0.0001 | - | |
|
| 2.3155 | 6370 | 0.0004 | - | |
|
| 2.3192 | 6380 | 0.0001 | - | |
|
| 2.3228 | 6390 | 0.0001 | - | |
|
| 2.3264 | 6400 | 0.0002 | - | |
|
| 2.3301 | 6410 | 0.0001 | - | |
|
| 2.3337 | 6420 | 0.0001 | - | |
|
| 2.3373 | 6430 | 0.0001 | - | |
|
| 2.3410 | 6440 | 0.0002 | - | |
|
| 2.3446 | 6450 | 0.0003 | - | |
|
| 2.3482 | 6460 | 0.0001 | - | |
|
| 2.3519 | 6470 | 0.0001 | - | |
|
| 2.3555 | 6480 | 0.0001 | - | |
|
| 2.3591 | 6490 | 0.0001 | - | |
|
| 2.3628 | 6500 | 0.0002 | - | |
|
| 2.3664 | 6510 | 0.0001 | - | |
|
| 2.3700 | 6520 | 0.0001 | - | |
|
| 2.3737 | 6530 | 0.0005 | - | |
|
| 2.3773 | 6540 | 0.0001 | - | |
|
| 2.3810 | 6550 | 0.0001 | - | |
|
| 2.3846 | 6560 | 0.0002 | - | |
|
| 2.3882 | 6570 | 0.0001 | - | |
|
| 2.3919 | 6580 | 0.0002 | - | |
|
| 2.3955 | 6590 | 0.0001 | - | |
|
| 2.3991 | 6600 | 0.0001 | - | |
|
| 2.4028 | 6610 | 0.0003 | - | |
|
| 2.4064 | 6620 | 0.0001 | - | |
|
| 2.4100 | 6630 | 0.0004 | - | |
|
| 2.4137 | 6640 | 0.0001 | - | |
|
| 2.4173 | 6650 | 0.0001 | - | |
|
| 2.4209 | 6660 | 0.0001 | - | |
|
| 2.4246 | 6670 | 0.0001 | - | |
|
| 2.4282 | 6680 | 0.0001 | - | |
|
| 2.4318 | 6690 | 0.0002 | - | |
|
| 2.4355 | 6700 | 0.0001 | - | |
|
| 2.4391 | 6710 | 0.0001 | - | |
|
| 2.4427 | 6720 | 0.0005 | - | |
|
| 2.4464 | 6730 | 0.0001 | - | |
|
| 2.4500 | 6740 | 0.0001 | - | |
|
| 2.4537 | 6750 | 0.0001 | - | |
|
| 2.4573 | 6760 | 0.0005 | - | |
|
| 2.4609 | 6770 | 0.0001 | - | |
|
| 2.4646 | 6780 | 0.0001 | - | |
|
| 2.4682 | 6790 | 0.0002 | - | |
|
| 2.4718 | 6800 | 0.0001 | - | |
|
| 2.4755 | 6810 | 0.0001 | - | |
|
| 2.4791 | 6820 | 0.0 | - | |
|
| 2.4827 | 6830 | 0.0001 | - | |
|
| 2.4864 | 6840 | 0.0001 | - | |
|
| 2.4900 | 6850 | 0.0004 | - | |
|
| 2.4936 | 6860 | 0.0002 | - | |
|
| 2.4973 | 6870 | 0.0002 | - | |
|
| 2.5009 | 6880 | 0.0001 | - | |
|
| 2.5045 | 6890 | 0.0001 | - | |
|
| 2.5082 | 6900 | 0.0001 | - | |
|
| 2.5118 | 6910 | 0.0002 | - | |
|
| 2.5154 | 6920 | 0.0002 | - | |
|
| 2.5191 | 6930 | 0.0001 | - | |
|
| 2.5227 | 6940 | 0.0001 | - | |
|
| 2.5264 | 6950 | 0.0001 | - | |
|
| 2.5300 | 6960 | 0.0 | - | |
|
| 2.5336 | 6970 | 0.0001 | - | |
|
| 2.5373 | 6980 | 0.0002 | - | |
|
| 2.5409 | 6990 | 0.0003 | - | |
|
| 2.5445 | 7000 | 0.0003 | - | |
|
| 2.5482 | 7010 | 0.0001 | - | |
|
| 2.5518 | 7020 | 0.0001 | - | |
|
| 2.5554 | 7030 | 0.0001 | - | |
|
| 2.5591 | 7040 | 0.0 | - | |
|
| 2.5627 | 7050 | 0.0001 | - | |
|
| 2.5663 | 7060 | 0.0001 | - | |
|
| 2.5700 | 7070 | 0.0004 | - | |
|
| 2.5736 | 7080 | 0.0001 | - | |
|
| 2.5772 | 7090 | 0.0002 | - | |
|
| 2.5809 | 7100 | 0.0001 | - | |
|
| 2.5845 | 7110 | 0.0001 | - | |
|
| 2.5881 | 7120 | 0.0 | - | |
|
| 2.5918 | 7130 | 0.0 | - | |
|
| 2.5954 | 7140 | 0.0001 | - | |
|
| 2.5991 | 7150 | 0.0001 | - | |
|
| 2.6027 | 7160 | 0.0 | - | |
|
| 2.6063 | 7170 | 0.0002 | - | |
|
| 2.6100 | 7180 | 0.0001 | - | |
|
| 2.6136 | 7190 | 0.0001 | - | |
|
| 2.6172 | 7200 | 0.0001 | - | |
|
| 2.6209 | 7210 | 0.0001 | - | |
|
| 2.6245 | 7220 | 0.0003 | - | |
|
| 2.6281 | 7230 | 0.0001 | - | |
|
| 2.6318 | 7240 | 0.0002 | - | |
|
| 2.6354 | 7250 | 0.0003 | - | |
|
| 2.6390 | 7260 | 0.0001 | - | |
|
| 2.6427 | 7270 | 0.0001 | - | |
|
| 2.6463 | 7280 | 0.0006 | - | |
|
| 2.6499 | 7290 | 0.0001 | - | |
|
| 2.6536 | 7300 | 0.0005 | - | |
|
| 2.6572 | 7310 | 0.0 | - | |
|
| 2.6609 | 7320 | 0.0001 | - | |
|
| 2.6645 | 7330 | 0.0001 | - | |
|
| 2.6681 | 7340 | 0.0001 | - | |
|
| 2.6718 | 7350 | 0.0001 | - | |
|
| 2.6754 | 7360 | 0.0002 | - | |
|
| 2.6790 | 7370 | 0.0001 | - | |
|
| 2.6827 | 7380 | 0.0001 | - | |
|
| 2.6863 | 7390 | 0.0001 | - | |
|
| 2.6899 | 7400 | 0.0005 | - | |
|
| 2.6936 | 7410 | 0.0001 | - | |
|
| 2.6972 | 7420 | 0.0002 | - | |
|
| 2.7008 | 7430 | 0.0001 | - | |
|
| 2.7045 | 7440 | 0.0001 | - | |
|
| 2.7081 | 7450 | 0.0002 | - | |
|
| 2.7117 | 7460 | 0.0006 | - | |
|
| 2.7154 | 7470 | 0.0002 | - | |
|
| 2.7190 | 7480 | 0.0 | - | |
|
| 2.7226 | 7490 | 0.0001 | - | |
|
| 2.7263 | 7500 | 0.0001 | - | |
|
| 2.7299 | 7510 | 0.0002 | - | |
|
| 2.7336 | 7520 | 0.0001 | - | |
|
| 2.7372 | 7530 | 0.0001 | - | |
|
| 2.7408 | 7540 | 0.0001 | - | |
|
| 2.7445 | 7550 | 0.0002 | - | |
|
| 2.7481 | 7560 | 0.0001 | - | |
|
| 2.7517 | 7570 | 0.0 | - | |
|
| 2.7554 | 7580 | 0.0001 | - | |
|
| 2.7590 | 7590 | 0.0001 | - | |
|
| 2.7626 | 7600 | 0.0 | - | |
|
| 2.7663 | 7610 | 0.0001 | - | |
|
| 2.7699 | 7620 | 0.0001 | - | |
|
| 2.7735 | 7630 | 0.0 | - | |
|
| 2.7772 | 7640 | 0.0002 | - | |
|
| 2.7808 | 7650 | 0.0001 | - | |
|
| 2.7844 | 7660 | 0.0001 | - | |
|
| 2.7881 | 7670 | 0.0 | - | |
|
| 2.7917 | 7680 | 0.0001 | - | |
|
| 2.7953 | 7690 | 0.0001 | - | |
|
| 2.7990 | 7700 | 0.0 | - | |
|
| 2.8026 | 7710 | 0.0002 | - | |
|
| 2.8063 | 7720 | 0.0001 | - | |
|
| 2.8099 | 7730 | 0.0 | - | |
|
| 2.8135 | 7740 | 0.0 | - | |
|
| 2.8172 | 7750 | 0.0001 | - | |
|
| 2.8208 | 7760 | 0.0001 | - | |
|
| 2.8244 | 7770 | 0.0 | - | |
|
| 2.8281 | 7780 | 0.0001 | - | |
|
| 2.8317 | 7790 | 0.0001 | - | |
|
| 2.8353 | 7800 | 0.0003 | - | |
|
| 2.8390 | 7810 | 0.0001 | - | |
|
| 2.8426 | 7820 | 0.0002 | - | |
|
| 2.8462 | 7830 | 0.0003 | - | |
|
| 2.8499 | 7840 | 0.0 | - | |
|
| 2.8535 | 7850 | 0.0001 | - | |
|
| 2.8571 | 7860 | 0.0 | - | |
|
| 2.8608 | 7870 | 0.0 | - | |
|
| 2.8644 | 7880 | 0.0002 | - | |
|
| 2.8680 | 7890 | 0.0001 | - | |
|
| 2.8717 | 7900 | 0.0001 | - | |
|
| 2.8753 | 7910 | 0.0001 | - | |
|
| 2.8790 | 7920 | 0.0002 | - | |
|
| 2.8826 | 7930 | 0.0001 | - | |
|
| 2.8862 | 7940 | 0.0 | - | |
|
| 2.8899 | 7950 | 0.0002 | - | |
|
| 2.8935 | 7960 | 0.0001 | - | |
|
| 2.8971 | 7970 | 0.0002 | - | |
|
| 2.9008 | 7980 | 0.0001 | - | |
|
| 2.9044 | 7990 | 0.0001 | - | |
|
| 2.9080 | 8000 | 0.0001 | - | |
|
| 2.9117 | 8010 | 0.0 | - | |
|
| 2.9153 | 8020 | 0.0001 | - | |
|
| 2.9189 | 8030 | 0.0001 | - | |
|
| 2.9226 | 8040 | 0.0001 | - | |
|
| 2.9262 | 8050 | 0.0001 | - | |
|
| 2.9298 | 8060 | 0.0001 | - | |
|
| 2.9335 | 8070 | 0.0001 | - | |
|
| 2.9371 | 8080 | 0.0001 | - | |
|
| 2.9407 | 8090 | 0.0001 | - | |
|
| 2.9444 | 8100 | 0.0001 | - | |
|
| 2.9480 | 8110 | 0.0001 | - | |
|
| 2.9517 | 8120 | 0.0003 | - | |
|
| 2.9553 | 8130 | 0.0001 | - | |
|
| 2.9589 | 8140 | 0.0001 | - | |
|
| 2.9626 | 8150 | 0.0001 | - | |
|
| 2.9662 | 8160 | 0.0005 | - | |
|
| 2.9698 | 8170 | 0.0005 | - | |
|
| 2.9735 | 8180 | 0.0001 | - | |
|
| 2.9771 | 8190 | 0.0001 | - | |
|
| 2.9807 | 8200 | 0.0002 | - | |
|
| 2.9844 | 8210 | 0.0001 | - | |
|
| 2.9880 | 8220 | 0.0001 | - | |
|
| 2.9916 | 8230 | 0.0001 | - | |
|
| 2.9953 | 8240 | 0.0001 | - | |
|
| 2.9989 | 8250 | 0.0001 | - | |
|
| 3.0 | 8253 | - | 0.0611 | |
|
| 3.0025 | 8260 | 0.0 | - | |
|
| 3.0062 | 8270 | 0.0001 | - | |
|
| 3.0098 | 8280 | 0.0001 | - | |
|
| 3.0134 | 8290 | 0.0002 | - | |
|
| 3.0171 | 8300 | 0.0001 | - | |
|
| 3.0207 | 8310 | 0.0001 | - | |
|
| 3.0244 | 8320 | 0.0002 | - | |
|
| 3.0280 | 8330 | 0.0001 | - | |
|
| 3.0316 | 8340 | 0.0001 | - | |
|
| 3.0353 | 8350 | 0.0002 | - | |
|
| 3.0389 | 8360 | 0.0001 | - | |
|
| 3.0425 | 8370 | 0.0001 | - | |
|
| 3.0462 | 8380 | 0.0001 | - | |
|
| 3.0498 | 8390 | 0.0001 | - | |
|
| 3.0534 | 8400 | 0.0001 | - | |
|
| 3.0571 | 8410 | 0.0001 | - | |
|
| 3.0607 | 8420 | 0.0001 | - | |
|
| 3.0643 | 8430 | 0.0001 | - | |
|
| 3.0680 | 8440 | 0.0 | - | |
|
| 3.0716 | 8450 | 0.0001 | - | |
|
| 3.0752 | 8460 | 0.0001 | - | |
|
| 3.0789 | 8470 | 0.0003 | - | |
|
| 3.0825 | 8480 | 0.0002 | - | |
|
| 3.0862 | 8490 | 0.0001 | - | |
|
| 3.0898 | 8500 | 0.0003 | - | |
|
| 3.0934 | 8510 | 0.0001 | - | |
|
| 3.0971 | 8520 | 0.0001 | - | |
|
| 3.1007 | 8530 | 0.0001 | - | |
|
| 3.1043 | 8540 | 0.0001 | - | |
|
| 3.1080 | 8550 | 0.0001 | - | |
|
| 3.1116 | 8560 | 0.0001 | - | |
|
| 3.1152 | 8570 | 0.0001 | - | |
|
| 3.1189 | 8580 | 0.0001 | - | |
|
| 3.1225 | 8590 | 0.0001 | - | |
|
| 3.1261 | 8600 | 0.0001 | - | |
|
| 3.1298 | 8610 | 0.0001 | - | |
|
| 3.1334 | 8620 | 0.0001 | - | |
|
| 3.1370 | 8630 | 0.0001 | - | |
|
| 3.1407 | 8640 | 0.0 | - | |
|
| 3.1443 | 8650 | 0.0004 | - | |
|
| 3.1479 | 8660 | 0.0001 | - | |
|
| 3.1516 | 8670 | 0.0002 | - | |
|
| 3.1552 | 8680 | 0.0001 | - | |
|
| 3.1589 | 8690 | 0.0 | - | |
|
| 3.1625 | 8700 | 0.0001 | - | |
|
| 3.1661 | 8710 | 0.0005 | - | |
|
| 3.1698 | 8720 | 0.0001 | - | |
|
| 3.1734 | 8730 | 0.0001 | - | |
|
| 3.1770 | 8740 | 0.0001 | - | |
|
| 3.1807 | 8750 | 0.0001 | - | |
|
| 3.1843 | 8760 | 0.0002 | - | |
|
| 3.1879 | 8770 | 0.0001 | - | |
|
| 3.1916 | 8780 | 0.0001 | - | |
|
| 3.1952 | 8790 | 0.0001 | - | |
|
| 3.1988 | 8800 | 0.0001 | - | |
|
| 3.2025 | 8810 | 0.0001 | - | |
|
| 3.2061 | 8820 | 0.0001 | - | |
|
| 3.2097 | 8830 | 0.0 | - | |
|
| 3.2134 | 8840 | 0.0 | - | |
|
| 3.2170 | 8850 | 0.0001 | - | |
|
| 3.2206 | 8860 | 0.0001 | - | |
|
| 3.2243 | 8870 | 0.0002 | - | |
|
| 3.2279 | 8880 | 0.0001 | - | |
|
| 3.2316 | 8890 | 0.0001 | - | |
|
| 3.2352 | 8900 | 0.0001 | - | |
|
| 3.2388 | 8910 | 0.0001 | - | |
|
| 3.2425 | 8920 | 0.0002 | - | |
|
| 3.2461 | 8930 | 0.0004 | - | |
|
| 3.2497 | 8940 | 0.0003 | - | |
|
| 3.2534 | 8950 | 0.0001 | - | |
|
| 3.2570 | 8960 | 0.0001 | - | |
|
| 3.2606 | 8970 | 0.0001 | - | |
|
| 3.2643 | 8980 | 0.0001 | - | |
|
| 3.2679 | 8990 | 0.0001 | - | |
|
| 3.2715 | 9000 | 0.0001 | - | |
|
| 3.2752 | 9010 | 0.0001 | - | |
|
| 3.2788 | 9020 | 0.0003 | - | |
|
| 3.2824 | 9030 | 0.0001 | - | |
|
| 3.2861 | 9040 | 0.0008 | - | |
|
| 3.2897 | 9050 | 0.0001 | - | |
|
| 3.2933 | 9060 | 0.0001 | - | |
|
| 3.2970 | 9070 | 0.0002 | - | |
|
| 3.3006 | 9080 | 0.0002 | - | |
|
| 3.3043 | 9090 | 0.0001 | - | |
|
| 3.3079 | 9100 | 0.0001 | - | |
|
| 3.3115 | 9110 | 0.0002 | - | |
|
| 3.3152 | 9120 | 0.0002 | - | |
|
| 3.3188 | 9130 | 0.0001 | - | |
|
| 3.3224 | 9140 | 0.0 | - | |
|
| 3.3261 | 9150 | 0.0001 | - | |
|
| 3.3297 | 9160 | 0.0001 | - | |
|
| 3.3333 | 9170 | 0.0001 | - | |
|
| 3.3370 | 9180 | 0.0001 | - | |
|
| 3.3406 | 9190 | 0.0001 | - | |
|
| 3.3442 | 9200 | 0.0001 | - | |
|
| 3.3479 | 9210 | 0.0003 | - | |
|
| 3.3515 | 9220 | 0.0001 | - | |
|
| 3.3551 | 9230 | 0.0 | - | |
|
| 3.3588 | 9240 | 0.0001 | - | |
|
| 3.3624 | 9250 | 0.0001 | - | |
|
| 3.3660 | 9260 | 0.0 | - | |
|
| 3.3697 | 9270 | 0.0001 | - | |
|
| 3.3733 | 9280 | 0.0001 | - | |
|
| 3.3770 | 9290 | 0.0001 | - | |
|
| 3.3806 | 9300 | 0.0001 | - | |
|
| 3.3842 | 9310 | 0.0 | - | |
|
| 3.3879 | 9320 | 0.0002 | - | |
|
| 3.3915 | 9330 | 0.0001 | - | |
|
| 3.3951 | 9340 | 0.0002 | - | |
|
| 3.3988 | 9350 | 0.0003 | - | |
|
| 3.4024 | 9360 | 0.0002 | - | |
|
| 3.4060 | 9370 | 0.0001 | - | |
|
| 3.4097 | 9380 | 0.0001 | - | |
|
| 3.4133 | 9390 | 0.0001 | - | |
|
| 3.4169 | 9400 | 0.0001 | - | |
|
| 3.4206 | 9410 | 0.0001 | - | |
|
| 3.4242 | 9420 | 0.0001 | - | |
|
| 3.4278 | 9430 | 0.0001 | - | |
|
| 3.4315 | 9440 | 0.0 | - | |
|
| 3.4351 | 9450 | 0.0001 | - | |
|
| 3.4387 | 9460 | 0.0001 | - | |
|
| 3.4424 | 9470 | 0.0001 | - | |
|
| 3.4460 | 9480 | 0.0001 | - | |
|
| 3.4497 | 9490 | 0.0001 | - | |
|
| 3.4533 | 9500 | 0.0001 | - | |
|
| 3.4569 | 9510 | 0.0001 | - | |
|
| 3.4606 | 9520 | 0.0001 | - | |
|
| 3.4642 | 9530 | 0.0002 | - | |
|
| 3.4678 | 9540 | 0.0001 | - | |
|
| 3.4715 | 9550 | 0.0001 | - | |
|
| 3.4751 | 9560 | 0.0001 | - | |
|
| 3.4787 | 9570 | 0.0001 | - | |
|
| 3.4824 | 9580 | 0.0 | - | |
|
| 3.4860 | 9590 | 0.0002 | - | |
|
| 3.4896 | 9600 | 0.0001 | - | |
|
| 3.4933 | 9610 | 0.0001 | - | |
|
| 3.4969 | 9620 | 0.0 | - | |
|
| 3.5005 | 9630 | 0.0001 | - | |
|
| 3.5042 | 9640 | 0.0001 | - | |
|
| 3.5078 | 9650 | 0.0001 | - | |
|
| 3.5115 | 9660 | 0.0001 | - | |
|
| 3.5151 | 9670 | 0.0001 | - | |
|
| 3.5187 | 9680 | 0.0002 | - | |
|
| 3.5224 | 9690 | 0.0003 | - | |
|
| 3.5260 | 9700 | 0.0001 | - | |
|
| 3.5296 | 9710 | 0.0 | - | |
|
| 3.5333 | 9720 | 0.0002 | - | |
|
| 3.5369 | 9730 | 0.0003 | - | |
|
| 3.5405 | 9740 | 0.0001 | - | |
|
| 3.5442 | 9750 | 0.0001 | - | |
|
| 3.5478 | 9760 | 0.0001 | - | |
|
| 3.5514 | 9770 | 0.0001 | - | |
|
| 3.5551 | 9780 | 0.0001 | - | |
|
| 3.5587 | 9790 | 0.0001 | - | |
|
| 3.5623 | 9800 | 0.0001 | - | |
|
| 3.5660 | 9810 | 0.0002 | - | |
|
| 3.5696 | 9820 | 0.0001 | - | |
|
| 3.5732 | 9830 | 0.0 | - | |
|
| 3.5769 | 9840 | 0.0 | - | |
|
| 3.5805 | 9850 | 0.0002 | - | |
|
| 3.5842 | 9860 | 0.0 | - | |
|
| 3.5878 | 9870 | 0.0001 | - | |
|
| 3.5914 | 9880 | 0.0001 | - | |
|
| 3.5951 | 9890 | 0.0001 | - | |
|
| 3.5987 | 9900 | 0.0001 | - | |
|
| 3.6023 | 9910 | 0.0001 | - | |
|
| 3.6060 | 9920 | 0.0002 | - | |
|
| 3.6096 | 9930 | 0.0001 | - | |
|
| 3.6132 | 9940 | 0.0 | - | |
|
| 3.6169 | 9950 | 0.0001 | - | |
|
| 3.6205 | 9960 | 0.0001 | - | |
|
| 3.6241 | 9970 | 0.0001 | - | |
|
| 3.6278 | 9980 | 0.0002 | - | |
|
| 3.6314 | 9990 | 0.0 | - | |
|
| 3.6350 | 10000 | 0.0 | - | |
|
| 3.6387 | 10010 | 0.0001 | - | |
|
| 3.6423 | 10020 | 0.0003 | - | |
|
| 3.6459 | 10030 | 0.0001 | - | |
|
| 3.6496 | 10040 | 0.0001 | - | |
|
| 3.6532 | 10050 | 0.0 | - | |
|
| 3.6569 | 10060 | 0.0001 | - | |
|
| 3.6605 | 10070 | 0.0 | - | |
|
| 3.6641 | 10080 | 0.0001 | - | |
|
| 3.6678 | 10090 | 0.0001 | - | |
|
| 3.6714 | 10100 | 0.0001 | - | |
|
| 3.6750 | 10110 | 0.0003 | - | |
|
| 3.6787 | 10120 | 0.0001 | - | |
|
| 3.6823 | 10130 | 0.0001 | - | |
|
| 3.6859 | 10140 | 0.0 | - | |
|
| 3.6896 | 10150 | 0.0001 | - | |
|
| 3.6932 | 10160 | 0.0001 | - | |
|
| 3.6968 | 10170 | 0.0001 | - | |
|
| 3.7005 | 10180 | 0.0001 | - | |
|
| 3.7041 | 10190 | 0.0 | - | |
|
| 3.7077 | 10200 | 0.0001 | - | |
|
| 3.7114 | 10210 | 0.0011 | - | |
|
| 3.7150 | 10220 | 0.0001 | - | |
|
| 3.7186 | 10230 | 0.0001 | - | |
|
| 3.7223 | 10240 | 0.0002 | - | |
|
| 3.7259 | 10250 | 0.0 | - | |
|
| 3.7296 | 10260 | 0.0001 | - | |
|
| 3.7332 | 10270 | 0.0 | - | |
|
| 3.7368 | 10280 | 0.0001 | - | |
|
| 3.7405 | 10290 | 0.0001 | - | |
|
| 3.7441 | 10300 | 0.0 | - | |
|
| 3.7477 | 10310 | 0.0001 | - | |
|
| 3.7514 | 10320 | 0.0 | - | |
|
| 3.7550 | 10330 | 0.0003 | - | |
|
| 3.7586 | 10340 | 0.0 | - | |
|
| 3.7623 | 10350 | 0.0003 | - | |
|
| 3.7659 | 10360 | 0.0 | - | |
|
| 3.7695 | 10370 | 0.0001 | - | |
|
| 3.7732 | 10380 | 0.0002 | - | |
|
| 3.7768 | 10390 | 0.0001 | - | |
|
| 3.7804 | 10400 | 0.0 | - | |
|
| 3.7841 | 10410 | 0.0001 | - | |
|
| 3.7877 | 10420 | 0.0002 | - | |
|
| 3.7913 | 10430 | 0.0005 | - | |
|
| 3.7950 | 10440 | 0.0001 | - | |
|
| 3.7986 | 10450 | 0.0001 | - | |
|
| 3.8023 | 10460 | 0.0 | - | |
|
| 3.8059 | 10470 | 0.0002 | - | |
|
| 3.8095 | 10480 | 0.0001 | - | |
|
| 3.8132 | 10490 | 0.0006 | - | |
|
| 3.8168 | 10500 | 0.0001 | - | |
|
| 3.8204 | 10510 | 0.0001 | - | |
|
| 3.8241 | 10520 | 0.0004 | - | |
|
| 3.8277 | 10530 | 0.0001 | - | |
|
| 3.8313 | 10540 | 0.0 | - | |
|
| 3.8350 | 10550 | 0.0001 | - | |
|
| 3.8386 | 10560 | 0.0 | - | |
|
| 3.8422 | 10570 | 0.0001 | - | |
|
| 3.8459 | 10580 | 0.0001 | - | |
|
| 3.8495 | 10590 | 0.0 | - | |
|
| 3.8531 | 10600 | 0.0001 | - | |
|
| 3.8568 | 10610 | 0.0001 | - | |
|
| 3.8604 | 10620 | 0.0001 | - | |
|
| 3.8640 | 10630 | 0.0001 | - | |
|
| 3.8677 | 10640 | 0.0001 | - | |
|
| 3.8713 | 10650 | 0.0001 | - | |
|
| 3.8750 | 10660 | 0.0001 | - | |
|
| 3.8786 | 10670 | 0.0001 | - | |
|
| 3.8822 | 10680 | 0.0 | - | |
|
| 3.8859 | 10690 | 0.0001 | - | |
|
| 3.8895 | 10700 | 0.0 | - | |
|
| 3.8931 | 10710 | 0.0001 | - | |
|
| 3.8968 | 10720 | 0.0001 | - | |
|
| 3.9004 | 10730 | 0.0001 | - | |
|
| 3.9040 | 10740 | 0.0 | - | |
|
| 3.9077 | 10750 | 0.0001 | - | |
|
| 3.9113 | 10760 | 0.0 | - | |
|
| 3.9149 | 10770 | 0.0 | - | |
|
| 3.9186 | 10780 | 0.0 | - | |
|
| 3.9222 | 10790 | 0.0001 | - | |
|
| 3.9258 | 10800 | 0.0001 | - | |
|
| 3.9295 | 10810 | 0.0003 | - | |
|
| 3.9331 | 10820 | 0.0001 | - | |
|
| 3.9368 | 10830 | 0.0005 | - | |
|
| 3.9404 | 10840 | 0.0001 | - | |
|
| 3.9440 | 10850 | 0.0001 | - | |
|
| 3.9477 | 10860 | 0.0 | - | |
|
| 3.9513 | 10870 | 0.0001 | - | |
|
| 3.9549 | 10880 | 0.0 | - | |
|
| 3.9586 | 10890 | 0.0001 | - | |
|
| 3.9622 | 10900 | 0.0 | - | |
|
| 3.9658 | 10910 | 0.0 | - | |
|
| 3.9695 | 10920 | 0.0 | - | |
|
| 3.9731 | 10930 | 0.0001 | - | |
|
| 3.9767 | 10940 | 0.0001 | - | |
|
| 3.9804 | 10950 | 0.0001 | - | |
|
| 3.9840 | 10960 | 0.0001 | - | |
|
| 3.9876 | 10970 | 0.0001 | - | |
|
| 3.9913 | 10980 | 0.0 | - | |
|
| 3.9949 | 10990 | 0.0001 | - | |
|
| 3.9985 | 11000 | 0.0001 | - | |
|
| 4.0 | 11004 | - | 0.0668 | |
|
|
|
* The bold row denotes the saved checkpoint. |
|
### Framework Versions |
|
- Python: 3.10.12 |
|
- SetFit: 1.0.3 |
|
- Sentence Transformers: 3.0.1 |
|
- Transformers: 4.37.0 |
|
- PyTorch: 2.5.1+cu121 |
|
- Datasets: 3.1.0 |
|
- Tokenizers: 0.15.2 |
|
|
|
## Citation |
|
|
|
### BibTeX |
|
```bibtex |
|
@article{https://doi.org/10.48550/arxiv.2209.11055, |
|
doi = {10.48550/ARXIV.2209.11055}, |
|
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} |
|
} |
|
``` |
|
|
|
<!-- |
|
## Glossary |
|
|
|
*Clearly define terms in order to be accessible across audiences.* |
|
--> |
|
|
|
<!-- |
|
## Model Card Authors |
|
|
|
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.* |
|
--> |
|
|
|
<!-- |
|
## Model Card Contact |
|
|
|
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.* |
|
--> |
