mann2107 commited on
Commit
6dd26af
1 Parent(s): 6c16ca6

Push model using huggingface_hub.

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Files changed (4) hide show
  1. README.md +512 -8
  2. config_setfit.json +2 -2
  3. model.safetensors +1 -1
  4. model_head.pkl +1 -1
README.md CHANGED
@@ -34,7 +34,7 @@ model-index:
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  split: test
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  metrics:
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  - type: silhouette_score
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- value: 0.4196937375508804
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  name: Silhouette_Score
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  ---
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@@ -88,7 +88,7 @@ The model has been trained using an efficient few-shot learning technique that i
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  ### Metrics
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  | Label | Silhouette_Score |
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  |:--------|:-----------------|
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- | **all** | 0.4197 |
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  ## Uses
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@@ -160,11 +160,11 @@ preds = model("Hello, Good morning, would you mind cancelling this rental car?")
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  | 13 | 24 |
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  ### Training Hyperparameters
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- - batch_size: (32, 32)
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- - num_epochs: (1, 1)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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- - num_iterations: 1
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  - body_learning_rate: (3e-05, 3e-05)
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  - head_learning_rate: 3e-05
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  - loss: MultipleNegativesRankingLoss
@@ -179,9 +179,513 @@ preds = model("Hello, Good morning, would you mind cancelling this rental car?")
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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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- | 0.0476 | 1 | 5.5459 | - |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
185
 
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  ### Framework Versions
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  - Python: 3.12.0
 
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  split: test
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  metrics:
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  - type: silhouette_score
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+ value: 0.6826105442176871
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  name: Silhouette_Score
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  ---
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88
  ### Metrics
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  | Label | Silhouette_Score |
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  |:--------|:-----------------|
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+ | **all** | 0.6826 |
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  ## Uses
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  | 13 | 24 |
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  ### Training Hyperparameters
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+ - batch_size: (8, 8)
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+ - num_epochs: (3, 3)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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+ - num_iterations: 100
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  - body_learning_rate: (3e-05, 3e-05)
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  - head_learning_rate: 3e-05
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  - loss: MultipleNegativesRankingLoss
 
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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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+ | 0.0001 | 1 | 2.5259 | - |
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+ | 0.0060 | 50 | 2.8997 | - |
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+ | 0.0119 | 100 | 2.8192 | - |
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+ | 0.0179 | 150 | 2.8803 | - |
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+ | 0.0238 | 200 | 2.635 | - |
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+ | 0.0298 | 250 | 2.5501 | - |
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+ | 0.0357 | 300 | 2.4468 | - |
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+ | 0.0417 | 350 | 2.1309 | - |
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+ | 0.0476 | 400 | 2.0439 | - |
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+ | 0.0536 | 450 | 1.9429 | - |
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+ | 0.0595 | 500 | 1.9344 | - |
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+ | 0.0655 | 550 | 1.8493 | - |
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+ | 0.0714 | 600 | 1.7907 | - |
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+ | 0.0774 | 650 | 1.7712 | - |
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+ | 0.0833 | 700 | 1.7349 | - |
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+ | 0.0893 | 750 | 1.7783 | - |
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+ | 0.0952 | 800 | 1.7022 | - |
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+ | 0.1012 | 850 | 1.6757 | - |
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+ | 0.1071 | 900 | 1.709 | - |
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+ | 0.1131 | 950 | 1.6231 | - |
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+ | 0.1190 | 1000 | 1.6647 | - |
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+ | 0.125 | 1050 | 1.7618 | - |
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+ | 0.1310 | 1100 | 1.652 | - |
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+ | 0.1369 | 1150 | 1.5564 | - |
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+ | 0.1429 | 1200 | 1.7067 | - |
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+ | 0.1488 | 1250 | 1.664 | - |
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+ | 0.1548 | 1300 | 1.7426 | - |
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+ | 0.1607 | 1350 | 1.6281 | - |
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+ | 0.1667 | 1400 | 1.6375 | - |
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+ | 0.1726 | 1450 | 1.6216 | - |
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+ | 0.1786 | 1500 | 1.5998 | - |
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+ | 0.1845 | 1550 | 1.4892 | - |
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+ | 0.1905 | 1600 | 1.556 | - |
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+ | 0.1964 | 1650 | 1.6657 | - |
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+ | 0.2024 | 1700 | 1.6113 | - |
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+ | 0.2083 | 1750 | 1.634 | - |
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+ | 0.2143 | 1800 | 1.6615 | - |
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+ | 0.2202 | 1850 | 1.5192 | - |
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+ | 0.2262 | 1900 | 1.5846 | - |
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+ | 0.2321 | 1950 | 1.5376 | - |
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+ | 0.2381 | 2000 | 1.6028 | - |
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+ | 0.2440 | 2050 | 1.5744 | - |
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+ | 0.25 | 2100 | 1.645 | - |
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+ | 0.2560 | 2150 | 1.5432 | - |
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+ | 0.2619 | 2200 | 1.5922 | - |
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+ | 0.2679 | 2250 | 1.612 | - |
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+ | 0.2738 | 2300 | 1.6553 | - |
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+ | 0.2798 | 2350 | 1.5797 | - |
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+ | 0.2857 | 2400 | 1.5249 | - |
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+ | 0.2917 | 2450 | 1.639 | - |
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+ | 0.2976 | 2500 | 1.7246 | - |
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+ | 0.3036 | 2550 | 1.6186 | - |
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+ | 0.3095 | 2600 | 1.537 | - |
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+ | 0.3155 | 2650 | 1.5701 | - |
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+ | 0.3214 | 2700 | 1.6095 | - |
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+ | 0.3274 | 2750 | 1.5344 | - |
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+ | 0.3333 | 2800 | 1.6029 | - |
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+ | 0.3393 | 2850 | 1.6141 | - |
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+ | 0.3452 | 2900 | 1.5655 | - |
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+ | 0.3512 | 2950 | 1.5892 | - |
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+ | 0.3571 | 3000 | 1.595 | - |
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+ | 0.3631 | 3050 | 1.5068 | - |
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+ | 0.3690 | 3100 | 1.5826 | - |
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+ | 0.375 | 3150 | 1.481 | - |
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+ | 0.3810 | 3200 | 1.6001 | - |
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+ | 0.3869 | 3250 | 1.4991 | - |
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+ | 0.3929 | 3300 | 1.605 | - |
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+ | 0.3988 | 3350 | 1.6154 | - |
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+ | 0.4048 | 3400 | 1.5516 | - |
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+ | 0.4107 | 3450 | 1.559 | - |
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+ | 0.4167 | 3500 | 1.559 | - |
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+ | 0.4226 | 3550 | 1.5725 | - |
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+ | 0.4286 | 3600 | 1.5719 | - |
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+ | 0.4345 | 3650 | 1.4918 | - |
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+ | 0.4405 | 3700 | 1.5816 | - |
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+ | 0.4464 | 3750 | 1.5017 | - |
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+ | 0.4524 | 3800 | 1.5093 | - |
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+ | 0.4583 | 3850 | 1.5705 | - |
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+ | 0.4643 | 3900 | 1.5584 | - |
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+ | 0.4702 | 3950 | 1.5328 | - |
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+ | 0.4762 | 4000 | 1.4932 | - |
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+ | 0.4821 | 4050 | 1.5907 | - |
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+ | 0.4881 | 4100 | 1.5339 | - |
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+ | 0.4940 | 4150 | 1.4954 | - |
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+ | 0.5 | 4200 | 1.5256 | - |
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+ | 0.5060 | 4250 | 1.5349 | - |
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+ | 0.5119 | 4300 | 1.5238 | - |
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+ | 0.5179 | 4350 | 1.5222 | - |
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+ | 0.5238 | 4400 | 1.6318 | - |
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+ | 0.5298 | 4450 | 1.5872 | - |
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+ | 0.5357 | 4500 | 1.4892 | - |
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+ | 0.5417 | 4550 | 1.5764 | - |
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+ | 0.5476 | 4600 | 1.6123 | - |
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+ | 0.5536 | 4650 | 1.4708 | - |
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+ | 0.5595 | 4700 | 1.5201 | - |
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+ | 0.5655 | 4750 | 1.4975 | - |
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+ | 0.5714 | 4800 | 1.5402 | - |
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+ | 0.5774 | 4850 | 1.5396 | - |
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+ | 0.5833 | 4900 | 1.5325 | - |
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+ | 0.5893 | 4950 | 1.5166 | - |
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+ | 0.5952 | 5000 | 1.5216 | - |
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+ | 0.6012 | 5050 | 1.5934 | - |
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+ | 0.6071 | 5100 | 1.5118 | - |
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+ | 0.6131 | 5150 | 1.6581 | - |
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+ | 0.6190 | 5200 | 1.4251 | - |
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+ | 0.625 | 5250 | 1.5259 | - |
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+ | 0.6310 | 5300 | 1.4854 | - |
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+ | 0.6369 | 5350 | 1.6242 | - |
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+ | 0.6429 | 5400 | 1.5234 | - |
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+ | 0.6488 | 5450 | 1.4594 | - |
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+ | 0.6548 | 5500 | 1.5513 | - |
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+ | 0.6607 | 5550 | 1.3946 | - |
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+ | 0.6667 | 5600 | 1.4795 | - |
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+ | 0.6726 | 5650 | 1.5203 | - |
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+ | 0.6786 | 5700 | 1.5137 | - |
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+ | 0.6845 | 5750 | 1.5305 | - |
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+ | 0.6905 | 5800 | 1.4958 | - |
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+ | 0.6964 | 5850 | 1.5028 | - |
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+ | 0.7024 | 5900 | 1.419 | - |
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+ | 0.7083 | 5950 | 1.5043 | - |
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+ | 0.7143 | 6000 | 1.4512 | - |
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+ | 0.7202 | 6050 | 1.5199 | - |
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+ | 0.7262 | 6100 | 1.5097 | - |
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+ | 0.7321 | 6150 | 1.4989 | - |
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+ | 0.7381 | 6200 | 1.4632 | - |
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+ | 0.7440 | 6250 | 1.4781 | - |
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+ | 0.75 | 6300 | 1.4592 | - |
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+ | 0.7560 | 6350 | 1.507 | - |
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+ | 0.7619 | 6400 | 1.5535 | - |
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+ | 0.7679 | 6450 | 1.3831 | - |
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+ | 0.7738 | 6500 | 1.572 | - |
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+ | 0.7798 | 6550 | 1.5461 | - |
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+ | 0.7857 | 6600 | 1.5142 | - |
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+ | 0.7917 | 6650 | 1.494 | - |
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+ | 0.7976 | 6700 | 1.5487 | - |
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+ | 0.8036 | 6750 | 1.4344 | - |
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+ | 0.8095 | 6800 | 1.5262 | - |
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+ | 0.8155 | 6850 | 1.4942 | - |
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+ | 0.8214 | 6900 | 1.54 | - |
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+ | 0.8274 | 6950 | 1.518 | - |
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+ | 0.8333 | 7000 | 1.5765 | - |
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+ | 0.8393 | 7050 | 1.5526 | - |
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+ | 0.8452 | 7100 | 1.5548 | - |
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+ | 0.8512 | 7150 | 1.3953 | - |
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+ | 0.8571 | 7200 | 1.5273 | - |
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+ | 0.8631 | 7250 | 1.4349 | - |
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+ | 0.8690 | 7300 | 1.4176 | - |
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+ | 0.875 | 7350 | 1.5242 | - |
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+ | 0.8810 | 7400 | 1.5263 | - |
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+ | 0.8869 | 7450 | 1.5435 | - |
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+ | 0.8929 | 7500 | 1.4882 | - |
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+ | 0.8988 | 7550 | 1.4965 | - |
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+ | 0.9048 | 7600 | 1.5185 | - |
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+ | 0.9107 | 7650 | 1.5739 | - |
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+ | 0.9167 | 7700 | 1.5821 | - |
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+ | 0.9226 | 7750 | 1.6197 | - |
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+ | 0.9286 | 7800 | 1.5154 | - |
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+ | 0.9345 | 7850 | 1.5844 | - |
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+ | 0.9405 | 7900 | 1.5242 | - |
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+ | 0.9464 | 7950 | 1.488 | - |
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+ | 0.9524 | 8000 | 1.5414 | - |
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+ | 0.9583 | 8050 | 1.4829 | - |
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+ | 0.9643 | 8100 | 1.5162 | - |
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+ | 0.9702 | 8150 | 1.4136 | - |
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+ | 0.9762 | 8200 | 1.36 | - |
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+ | 0.9821 | 8250 | 1.5511 | - |
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+ | 0.9881 | 8300 | 1.4908 | - |
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+ | 0.9940 | 8350 | 1.5312 | - |
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+ | 1.0 | 8400 | 1.5008 | - |
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+ | 1.0060 | 8450 | 1.4283 | - |
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+ | 1.0119 | 8500 | 1.5027 | - |
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+ | 1.0179 | 8550 | 1.48 | - |
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+ | 1.0238 | 8600 | 1.425 | - |
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+ | 1.0298 | 8650 | 1.5233 | - |
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+ | 1.0357 | 8700 | 1.4259 | - |
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+ | 1.0417 | 8750 | 1.4355 | - |
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+ | 1.0476 | 8800 | 1.5006 | - |
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+ | 1.0536 | 8850 | 1.511 | - |
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+ | 1.0595 | 8900 | 1.3043 | - |
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+ | 1.0655 | 8950 | 1.5039 | - |
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+ | 1.0714 | 9000 | 1.4909 | - |
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+ | 1.0774 | 9050 | 1.4493 | - |
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+ | 1.0833 | 9100 | 1.4877 | - |
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+ | 1.0893 | 9150 | 1.5232 | - |
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+ | 1.0952 | 9200 | 1.6282 | - |
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+ | 1.1012 | 9250 | 1.4438 | - |
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+ | 1.1071 | 9300 | 1.5234 | - |
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+ | 1.1131 | 9350 | 1.5368 | - |
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+ | 1.1190 | 9400 | 1.5029 | - |
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+ | 1.125 | 9450 | 1.4776 | - |
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+ | 1.1310 | 9500 | 1.4877 | - |
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+ | 1.1369 | 9550 | 1.4917 | - |
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+ | 1.1429 | 9600 | 1.4474 | - |
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+ | 1.1488 | 9650 | 1.3519 | - |
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+ | 1.1548 | 9700 | 1.5118 | - |
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+ | 1.1607 | 9750 | 1.5507 | - |
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+ | 1.1667 | 9800 | 1.4395 | - |
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+ | 1.1726 | 9850 | 1.4883 | - |
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+ | 1.1786 | 9900 | 1.4524 | - |
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+ | 1.1845 | 9950 | 1.4756 | - |
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+ | 1.1905 | 10000 | 1.5255 | - |
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+ | 1.1964 | 10050 | 1.4795 | - |
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+ | 1.2024 | 10100 | 1.5277 | - |
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+ | 1.2083 | 10150 | 1.477 | - |
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+ | 1.2143 | 10200 | 1.4438 | - |
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+ | 1.2202 | 10250 | 1.5517 | - |
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+ | 1.2262 | 10300 | 1.588 | - |
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+ | 1.2321 | 10350 | 1.5352 | - |
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+ | 1.2381 | 10400 | 1.3697 | - |
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+ | 1.2440 | 10450 | 1.4449 | - |
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+ | 1.25 | 10500 | 1.4473 | - |
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+ | 1.2560 | 10550 | 1.5566 | - |
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+ | 1.2619 | 10600 | 1.4502 | - |
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+ | 1.2679 | 10650 | 1.4821 | - |
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+ | 1.2738 | 10700 | 1.4296 | - |
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+ | 1.2798 | 10750 | 1.4801 | - |
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+ | 1.2857 | 10800 | 1.4542 | - |
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+ | 1.2917 | 10850 | 1.4258 | - |
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+ | 1.2976 | 10900 | 1.4142 | - |
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+ | 1.3036 | 10950 | 1.6023 | - |
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+ | 1.3095 | 11000 | 1.4291 | - |
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+ | 1.3155 | 11050 | 1.5386 | - |
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+ | 1.3214 | 11100 | 1.4433 | - |
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+ | 1.3274 | 11150 | 1.4218 | - |
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+ | 1.3333 | 11200 | 1.4345 | - |
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+ | 1.3393 | 11250 | 1.5321 | - |
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+ | 1.3452 | 11300 | 1.5001 | - |
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+ | 1.3512 | 11350 | 1.3381 | - |
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+ | 1.3571 | 11400 | 1.4819 | - |
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+ | 1.3631 | 11450 | 1.4676 | - |
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+ | 1.3690 | 11500 | 1.5056 | - |
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+ | 1.375 | 11550 | 1.5052 | - |
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+ | 1.3810 | 11600 | 1.5217 | - |
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+ | 1.3869 | 11650 | 1.391 | - |
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+ | 1.3929 | 11700 | 1.46 | - |
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+ | 1.3988 | 11750 | 1.5022 | - |
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+ | 1.4048 | 11800 | 1.4579 | - |
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+ | 1.4107 | 11850 | 1.5025 | - |
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+ | 1.4167 | 11900 | 1.5058 | - |
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+ | 1.4226 | 11950 | 1.5107 | - |
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+ | 1.4286 | 12000 | 1.5327 | - |
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+ | 1.4345 | 12050 | 1.4727 | - |
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+ | 1.4405 | 12100 | 1.4353 | - |
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+ | 1.4464 | 12150 | 1.42 | - |
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+ | 1.4524 | 12200 | 1.5349 | - |
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+ | 1.4583 | 12250 | 1.473 | - |
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+ | 1.4643 | 12300 | 1.5228 | - |
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+ | 1.4702 | 12350 | 1.498 | - |
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+ | 1.4762 | 12400 | 1.4321 | - |
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+ | 1.4821 | 12450 | 1.5058 | - |
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+ | 1.4881 | 12500 | 1.4601 | - |
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+ | 1.4940 | 12550 | 1.5346 | - |
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+ | 1.5 | 12600 | 1.5985 | - |
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+ | 1.5060 | 12650 | 1.4683 | - |
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+ | 1.5119 | 12700 | 1.5088 | - |
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+ | 1.5179 | 12750 | 1.5082 | - |
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+ | 1.5238 | 12800 | 1.5784 | - |
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+ | 1.5298 | 12850 | 1.5241 | - |
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+ | 1.5357 | 12900 | 1.434 | - |
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+ | 1.5417 | 12950 | 1.452 | - |
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+ | 1.5476 | 13000 | 1.4459 | - |
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+ | 1.5536 | 13050 | 1.4965 | - |
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+ | 1.5595 | 13100 | 1.5313 | - |
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+ | 1.5655 | 13150 | 1.4781 | - |
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+ | 1.5714 | 13200 | 1.5502 | - |
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+ | 1.5774 | 13250 | 1.4602 | - |
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+ | 1.5833 | 13300 | 1.4477 | - |
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+ | 1.5893 | 13350 | 1.4736 | - |
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+ | 1.5952 | 13400 | 1.5035 | - |
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+ | 1.6012 | 13450 | 1.4829 | - |
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+ | 1.6071 | 13500 | 1.4941 | - |
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+ | 1.6131 | 13550 | 1.5462 | - |
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+ | 1.6190 | 13600 | 1.4764 | - |
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+ | 1.625 | 13650 | 1.4838 | - |
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+ | 1.6310 | 13700 | 1.4264 | - |
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+ | 1.6369 | 13750 | 1.6312 | - |
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+ | 1.6429 | 13800 | 1.4323 | - |
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+ | 1.6488 | 13850 | 1.514 | - |
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+ | 1.6548 | 13900 | 1.3944 | - |
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+ | 1.6607 | 13950 | 1.4709 | - |
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+ | 1.6667 | 14000 | 1.4268 | - |
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+ | 1.6726 | 14050 | 1.5699 | - |
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+ | 1.6786 | 14100 | 1.5433 | - |
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+ | 1.6845 | 14150 | 1.431 | - |
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+ | 1.6905 | 14200 | 1.5421 | - |
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+ | 1.6964 | 14250 | 1.4854 | - |
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+ | 1.7024 | 14300 | 1.4341 | - |
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+ | 1.7083 | 14350 | 1.4321 | - |
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+ | 1.7143 | 14400 | 1.4284 | - |
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+ | 1.7202 | 14450 | 1.4725 | - |
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+ | 1.7262 | 14500 | 1.5744 | - |
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+ | 1.7321 | 14550 | 1.4892 | - |
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+ | 1.7381 | 14600 | 1.5357 | - |
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+ | 1.7440 | 14650 | 1.4536 | - |
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+ | 1.75 | 14700 | 1.4861 | - |
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+ | 1.7560 | 14750 | 1.5268 | - |
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+ | 1.7619 | 14800 | 1.4613 | - |
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+ | 1.7679 | 14850 | 1.4313 | - |
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+ | 1.7738 | 14900 | 1.4522 | - |
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+ | 1.7798 | 14950 | 1.4291 | - |
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+ | 1.7857 | 15000 | 1.5054 | - |
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+ | 1.7917 | 15050 | 1.495 | - |
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+ | 1.7976 | 15100 | 1.5352 | - |
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+ | 1.8036 | 15150 | 1.4803 | - |
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+ | 1.8095 | 15200 | 1.3922 | - |
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+ | 1.8155 | 15250 | 1.4879 | - |
490
+ | 1.8214 | 15300 | 1.4752 | - |
491
+ | 1.8274 | 15350 | 1.5102 | - |
492
+ | 1.8333 | 15400 | 1.4474 | - |
493
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494
+ | 1.8452 | 15500 | 1.5216 | - |
495
+ | 1.8512 | 15550 | 1.4656 | - |
496
+ | 1.8571 | 15600 | 1.5171 | - |
497
+ | 1.8631 | 15650 | 1.3437 | - |
498
+ | 1.8690 | 15700 | 1.4875 | - |
499
+ | 1.875 | 15750 | 1.4692 | - |
500
+ | 1.8810 | 15800 | 1.4804 | - |
501
+ | 1.8869 | 15850 | 1.4423 | - |
502
+ | 1.8929 | 15900 | 1.4592 | - |
503
+ | 1.8988 | 15950 | 1.5764 | - |
504
+ | 1.9048 | 16000 | 1.4083 | - |
505
+ | 1.9107 | 16050 | 1.4852 | - |
506
+ | 1.9167 | 16100 | 1.5158 | - |
507
+ | 1.9226 | 16150 | 1.4602 | - |
508
+ | 1.9286 | 16200 | 1.4465 | - |
509
+ | 1.9345 | 16250 | 1.412 | - |
510
+ | 1.9405 | 16300 | 1.483 | - |
511
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512
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513
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514
+ | 1.9643 | 16500 | 1.6241 | - |
515
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516
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517
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518
+ | 1.9881 | 16700 | 1.457 | - |
519
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520
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521
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522
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523
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524
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525
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526
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527
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528
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529
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530
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531
+ | 2.0655 | 17350 | 1.4825 | - |
532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
+ | 2.1964 | 18450 | 1.3559 | - |
554
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555
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556
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557
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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581
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582
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583
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584
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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599
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600
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601
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602
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603
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604
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605
+ | 2.5060 | 21050 | 1.5522 | - |
606
+ | 2.5119 | 21100 | 1.3759 | - |
607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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640
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641
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644
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645
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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668
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669
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690
  ### Framework Versions
691
  - Python: 3.12.0
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