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Hulyyy
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req-quality-setfit-128

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files
xet
 Community
Hulyyy commited on
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  1. README.md +433 -327
  2. model.safetensors +1 -1
  3. model_head.pkl +1 -1
README.md CHANGED
@@ -34,16 +34,16 @@ model-index:
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  split: test
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  metrics:
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  - type: micro_f1
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- value: 0.5705128205128205
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  name: Micro_F1
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  - type: macro_f1
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- value: 0.5793040286957435
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  name: Macro_F1
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  - type: hamming_accuracy
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- value: 0.8897119341563786
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  name: Hamming_Accuracy
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  - type: subset_accuracy
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- value: 0.5720164609053497
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  name: Subset_Accuracy
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  ---
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@@ -79,7 +79,7 @@ The model has been trained using an efficient few-shot learning technique that i
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  ### Metrics
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  | Label | Micro_F1 | Macro_F1 | Hamming_Accuracy | Subset_Accuracy |
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  |:--------|:---------|:---------|:-----------------|:----------------|
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- | **all** | 0.5705 | 0.5793 | 0.8897 | 0.5720 |
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  ## Uses
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@@ -138,7 +138,7 @@ preds = model("The product shall store new conference rooms.")
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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: 150
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  - body_learning_rate: (1e-05, 1e-05)
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  - head_learning_rate: 1e-05
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  - loss: CosineSimilarityLoss
@@ -155,327 +155,433 @@ preds = model("The product shall store new conference rooms.")
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  ### Training Results
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  | Epoch | Step | Training Loss | Validation Loss |
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  |:------:|:-----:|:-------------:|:---------------:|
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- | 0.0002 | 1 | 0.3465 | - |
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- | 0.0094 | 50 | 0.3586 | - |
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- | 0.0187 | 100 | 0.3442 | - |
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- | 0.0281 | 150 | 0.3214 | - |
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- | 0.0375 | 200 | 0.2907 | - |
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- | 0.0469 | 250 | 0.2647 | - |
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- | 0.0562 | 300 | 0.2612 | - |
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- | 0.0656 | 350 | 0.2543 | - |
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- | 0.0750 | 400 | 0.2507 | - |
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- | 0.0843 | 450 | 0.2483 | - |
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- | 0.0937 | 500 | 0.2435 | - |
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- | 0.1031 | 550 | 0.2409 | - |
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- | 0.1125 | 600 | 0.2329 | - |
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- | 0.1218 | 650 | 0.2318 | - |
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- | 0.1312 | 700 | 0.2292 | - |
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- | 0.1406 | 750 | 0.226 | - |
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- | 0.1500 | 800 | 0.2194 | - |
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- | 0.1593 | 850 | 0.2184 | - |
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- | 0.1687 | 900 | 0.2135 | - |
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- | 0.1781 | 950 | 0.2133 | - |
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- | 0.1874 | 1000 | 0.2052 | - |
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- | 0.1968 | 1050 | 0.2019 | - |
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- | 0.2062 | 1100 | 0.1977 | - |
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- | 0.2156 | 1150 | 0.196 | - |
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- | 0.2249 | 1200 | 0.185 | - |
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- | 0.2343 | 1250 | 0.1812 | - |
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- | 0.2437 | 1300 | 0.1747 | - |
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- | 0.2530 | 1350 | 0.1756 | - |
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- | 0.2624 | 1400 | 0.1634 | - |
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- | 0.2718 | 1450 | 0.158 | - |
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- | 0.2812 | 1500 | 0.1502 | - |
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- | 0.2905 | 1550 | 0.1433 | - |
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- | 0.2999 | 1600 | 0.1305 | - |
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- | 0.3093 | 1650 | 0.1333 | - |
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- | 0.3187 | 1700 | 0.1115 | - |
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- | 0.3280 | 1750 | 0.1073 | - |
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- | 0.3374 | 1800 | 0.1016 | - |
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- | 0.3468 | 1850 | 0.0978 | - |
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- | 0.3561 | 1900 | 0.0861 | - |
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- | 0.3655 | 1950 | 0.0767 | - |
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- | 0.3749 | 2000 | 0.0733 | - |
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- | 0.3843 | 2050 | 0.0676 | - |
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- | 0.3936 | 2100 | 0.061 | - |
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- | 0.4030 | 2150 | 0.0594 | - |
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- | 0.4124 | 2200 | 0.0575 | - |
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- | 0.4217 | 2250 | 0.0526 | - |
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- | 0.4311 | 2300 | 0.0484 | - |
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- | 0.4405 | 2350 | 0.043 | - |
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- | 0.4499 | 2400 | 0.0424 | - |
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- | 0.4592 | 2450 | 0.0396 | - |
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- | 0.4686 | 2500 | 0.0435 | - |
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- | 0.4780 | 2550 | 0.0361 | - |
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- | 0.4873 | 2600 | 0.0354 | - |
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- | 0.4967 | 2650 | 0.0372 | - |
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- | 0.5061 | 2700 | 0.0342 | - |
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- | 0.5155 | 2750 | 0.0342 | - |
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- | 0.5248 | 2800 | 0.0314 | - |
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- | 0.5342 | 2850 | 0.0296 | - |
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- | 0.5436 | 2900 | 0.0316 | - |
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- | 0.5530 | 2950 | 0.0295 | - |
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- | 0.5623 | 3000 | 0.0271 | - |
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- | 0.5717 | 3050 | 0.0278 | - |
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- | 0.5811 | 3100 | 0.0293 | - |
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- | 0.5904 | 3150 | 0.025 | - |
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- | 0.5998 | 3200 | 0.024 | - |
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- | 0.6092 | 3250 | 0.0233 | - |
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- | 0.6186 | 3300 | 0.0237 | - |
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- | 0.6279 | 3350 | 0.0249 | - |
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- | 0.6373 | 3400 | 0.0228 | - |
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- | 0.6467 | 3450 | 0.0265 | - |
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- | 0.6560 | 3500 | 0.0208 | - |
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- | 0.6654 | 3550 | 0.0249 | - |
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- | 0.6748 | 3600 | 0.0241 | - |
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- | 0.6842 | 3650 | 0.0211 | - |
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- | 0.6935 | 3700 | 0.0202 | - |
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- | 0.7029 | 3750 | 0.0212 | - |
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- | 0.7123 | 3800 | 0.0203 | - |
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- | 0.7216 | 3850 | 0.0206 | - |
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- | 0.7310 | 3900 | 0.0188 | - |
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- | 0.7404 | 3950 | 0.0192 | - |
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- | 0.7498 | 4000 | 0.0193 | - |
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- | 0.7591 | 4050 | 0.0182 | - |
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- | 0.7685 | 4100 | 0.0177 | - |
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- | 0.7779 | 4150 | 0.0154 | - |
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- | 0.7873 | 4200 | 0.0147 | - |
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- | 0.7966 | 4250 | 0.0148 | - |
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- | 0.8060 | 4300 | 0.0139 | - |
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- | 0.8154 | 4350 | 0.0129 | - |
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- | 0.8247 | 4400 | 0.0125 | - |
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- | 0.8341 | 4450 | 0.0123 | - |
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- | 0.8435 | 4500 | 0.0112 | - |
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- | 0.8529 | 4550 | 0.0104 | - |
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- | 0.8622 | 4600 | 0.0107 | - |
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- | 0.8716 | 4650 | 0.0097 | - |
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- | 0.8810 | 4700 | 0.0101 | - |
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- | 0.8903 | 4750 | 0.0112 | - |
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- | 0.8997 | 4800 | 0.0088 | - |
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- | 0.9091 | 4850 | 0.0085 | - |
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- | 0.9185 | 4900 | 0.0086 | - |
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- | 0.9278 | 4950 | 0.0105 | - |
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- | 0.9372 | 5000 | 0.0089 | - |
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- | 0.9466 | 5050 | 0.0069 | - |
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- | 0.9560 | 5100 | 0.0084 | - |
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- | 0.9653 | 5150 | 0.0081 | - |
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- | 0.9747 | 5200 | 0.008 | - |
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- | 0.9841 | 5250 | 0.0077 | - |
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- | 0.9934 | 5300 | 0.0086 | - |
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- | 1.0028 | 5350 | 0.0069 | - |
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- | 1.0122 | 5400 | 0.0059 | - |
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- | 1.0216 | 5450 | 0.0062 | - |
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- | 1.0309 | 5500 | 0.0063 | - |
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- | 1.0403 | 5550 | 0.0065 | - |
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- | 1.0497 | 5600 | 0.0072 | - |
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- | 1.0590 | 5650 | 0.0063 | - |
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- | 1.0684 | 5700 | 0.0066 | - |
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- | 1.0778 | 5750 | 0.0068 | - |
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- | 1.0872 | 5800 | 0.0058 | - |
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- | 1.0965 | 5850 | 0.0056 | - |
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- | 1.1059 | 5900 | 0.0043 | - |
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- | 1.1153 | 5950 | 0.0053 | - |
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- | 1.1246 | 6000 | 0.0061 | - |
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- | 1.1340 | 6050 | 0.0053 | - |
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- | 1.1434 | 6100 | 0.0057 | - |
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- | 1.1528 | 6150 | 0.004 | - |
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- | 1.1621 | 6200 | 0.0052 | - |
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- | 1.1715 | 6250 | 0.0048 | - |
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- | 1.1809 | 6300 | 0.0055 | - |
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- | 1.1903 | 6350 | 0.0054 | - |
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- | 1.1996 | 6400 | 0.0057 | - |
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- | 1.2090 | 6450 | 0.0053 | - |
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- | 1.2184 | 6500 | 0.0044 | - |
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- | 1.2277 | 6550 | 0.0057 | - |
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- | 1.2371 | 6600 | 0.004 | - |
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- | 1.2465 | 6650 | 0.0054 | - |
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- | 1.2559 | 6700 | 0.0056 | - |
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- | 1.2652 | 6750 | 0.0044 | - |
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- | 1.2746 | 6800 | 0.004 | - |
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- | 1.2840 | 6850 | 0.0045 | - |
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- | 1.2933 | 6900 | 0.0051 | - |
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- | 1.3027 | 6950 | 0.0052 | - |
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- | 1.3121 | 7000 | 0.0043 | - |
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- | 1.3215 | 7050 | 0.0037 | - |
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- | 1.3308 | 7100 | 0.004 | - |
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- | 1.3402 | 7150 | 0.004 | - |
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- | 1.3496 | 7200 | 0.0043 | - |
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- | 1.3590 | 7250 | 0.004 | - |
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- | 1.3683 | 7300 | 0.0041 | - |
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- | 1.3777 | 7350 | 0.0049 | - |
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- | 1.3871 | 7400 | 0.0032 | - |
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- | 1.3964 | 7450 | 0.0037 | - |
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- | 1.4058 | 7500 | 0.0039 | - |
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- | 1.4152 | 7550 | 0.0035 | - |
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- | 1.4246 | 7600 | 0.0031 | - |
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- | 1.4339 | 7650 | 0.0032 | - |
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- | 1.4433 | 7700 | 0.0033 | - |
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- | 1.4527 | 7750 | 0.0037 | - |
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- | 1.4620 | 7800 | 0.004 | - |
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- | 1.4714 | 7850 | 0.0027 | - |
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- | 1.4808 | 7900 | 0.0035 | - |
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- | 1.4902 | 7950 | 0.0026 | - |
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- | 1.4995 | 8000 | 0.0031 | - |
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- | 1.5089 | 8050 | 0.0027 | - |
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- | 1.5183 | 8100 | 0.0033 | - |
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- | 1.5276 | 8150 | 0.0029 | - |
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- | 1.5370 | 8200 | 0.003 | - |
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- | 1.5464 | 8250 | 0.0031 | - |
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- | 1.5558 | 8300 | 0.0025 | - |
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- | 1.5651 | 8350 | 0.0026 | - |
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- | 1.5745 | 8400 | 0.0031 | - |
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- | 1.5839 | 8450 | 0.0026 | - |
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- | 1.5933 | 8500 | 0.0027 | - |
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- | 1.6026 | 8550 | 0.0026 | - |
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- | 1.6120 | 8600 | 0.0025 | - |
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- | 1.6214 | 8650 | 0.0024 | - |
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- | 1.6307 | 8700 | 0.0026 | - |
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- | 1.6401 | 8750 | 0.0022 | - |
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- | 1.6495 | 8800 | 0.0023 | - |
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- | 1.6589 | 8850 | 0.0023 | - |
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- | 1.6682 | 8900 | 0.0023 | - |
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- | 1.6776 | 8950 | 0.0026 | - |
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- | 1.6870 | 9000 | 0.0022 | - |
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- | 1.6963 | 9050 | 0.0022 | - |
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- | 1.7057 | 9100 | 0.0017 | - |
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- | 1.7151 | 9150 | 0.0022 | - |
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- | 1.7245 | 9200 | 0.0029 | - |
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- | 1.7338 | 9250 | 0.0018 | - |
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- | 1.7432 | 9300 | 0.0024 | - |
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- | 1.7526 | 9350 | 0.0024 | - |
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- | 1.7619 | 9400 | 0.0021 | - |
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- | 1.7713 | 9450 | 0.0022 | - |
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- | 1.7807 | 9500 | 0.0019 | - |
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- | 1.7901 | 9550 | 0.0019 | - |
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- | 1.7994 | 9600 | 0.0018 | - |
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- | 1.8088 | 9650 | 0.0022 | - |
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- | 1.8182 | 9700 | 0.0018 | - |
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- | 1.8276 | 9750 | 0.0019 | - |
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- | 1.8369 | 9800 | 0.0018 | - |
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- | 1.8463 | 9850 | 0.0012 | - |
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- | 1.8557 | 9900 | 0.0016 | - |
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- | 1.8650 | 9950 | 0.0019 | - |
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- | 1.8744 | 10000 | 0.0015 | - |
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- | 1.8838 | 10050 | 0.0019 | - |
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- | 1.8932 | 10100 | 0.0014 | - |
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- | 1.9025 | 10150 | 0.0016 | - |
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- | 1.9119 | 10200 | 0.0019 | - |
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- | 1.9213 | 10250 | 0.0018 | - |
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- | 1.9306 | 10300 | 0.0012 | - |
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- | 1.9400 | 10350 | 0.0015 | - |
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- | 1.9494 | 10400 | 0.0017 | - |
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- | 1.9588 | 10450 | 0.0015 | - |
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- | 1.9775 | 10550 | 0.0019 | - |
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- | 1.9869 | 10600 | 0.0018 | - |
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- | 1.9963 | 10650 | 0.0014 | - |
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- | 2.0056 | 10700 | 0.0015 | - |
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- | 2.0150 | 10750 | 0.0011 | - |
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- | 2.0244 | 10800 | 0.0014 | - |
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- | 2.0337 | 10850 | 0.0014 | - |
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- | 2.0431 | 10900 | 0.0014 | - |
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- | 2.0525 | 10950 | 0.0017 | - |
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- | 2.0619 | 11000 | 0.0014 | - |
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- | 2.0712 | 11050 | 0.0015 | - |
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- | 2.0806 | 11100 | 0.0013 | - |
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- | 2.0900 | 11150 | 0.001 | - |
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- | 2.0993 | 11200 | 0.0016 | - |
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- | 2.1181 | 11300 | 0.0015 | - |
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- | 2.1462 | 11450 | 0.0014 | - |
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- | 2.1649 | 11550 | 0.0013 | - |
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- | 2.1743 | 11600 | 0.0011 | - |
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- | 2.2024 | 11750 | 0.0013 | - |
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- | 2.2118 | 11800 | 0.0012 | - |
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- | 2.2212 | 11850 | 0.0011 | - |
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- | 2.2306 | 11900 | 0.0014 | - |
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- | 2.2493 | 12000 | 0.0015 | - |
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- | 2.2587 | 12050 | 0.0012 | - |
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- | 2.2680 | 12100 | 0.0011 | - |
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- | 2.2774 | 12150 | 0.0007 | - |
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- | 2.2868 | 12200 | 0.0011 | - |
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- | 2.2962 | 12250 | 0.0015 | - |
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- | 2.3055 | 12300 | 0.0011 | - |
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- | 2.3149 | 12350 | 0.0011 | - |
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- | 2.3243 | 12400 | 0.0012 | - |
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- | 2.3336 | 12450 | 0.0009 | - |
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- | 2.3805 | 12700 | 0.0008 | - |
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- | 2.3993 | 12800 | 0.0009 | - |
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- | 2.5023 | 13350 | 0.0012 | - |
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- | 2.5211 | 13450 | 0.0009 | - |
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- | 2.5492 | 13600 | 0.001 | - |
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- | 2.5586 | 13650 | 0.0012 | - |
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- | 2.5679 | 13700 | 0.0009 | - |
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- | 2.5773 | 13750 | 0.0007 | - |
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- | 2.5867 | 13800 | 0.0006 | - |
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- | 2.5961 | 13850 | 0.0007 | - |
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- | 2.6054 | 13900 | 0.0006 | - |
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- | 2.6148 | 13950 | 0.0013 | - |
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- | 2.6242 | 14000 | 0.0008 | - |
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- | 2.6336 | 14050 | 0.0012 | - |
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- | 2.6429 | 14100 | 0.0008 | - |
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- | 2.6523 | 14150 | 0.0008 | - |
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- | 2.6617 | 14200 | 0.001 | - |
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- | 2.6710 | 14250 | 0.0008 | - |
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- | 2.6804 | 14300 | 0.0008 | - |
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- | 2.6898 | 14350 | 0.0008 | - |
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- | 2.6992 | 14400 | 0.0008 | - |
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- | 2.7085 | 14450 | 0.0011 | - |
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- | 2.7179 | 14500 | 0.001 | - |
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- | 2.7273 | 14550 | 0.0012 | - |
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- | 2.7366 | 14600 | 0.0012 | - |
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- | 2.7460 | 14650 | 0.0009 | - |
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- | 2.7554 | 14700 | 0.0008 | - |
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- | 2.7648 | 14750 | 0.0012 | - |
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- | 2.7741 | 14800 | 0.0008 | - |
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- | 2.7835 | 14850 | 0.0011 | - |
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- | 2.7929 | 14900 | 0.0009 | - |
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- | 2.8022 | 14950 | 0.0011 | - |
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- | 2.8116 | 15000 | 0.0009 | - |
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- | 2.8210 | 15050 | 0.0011 | - |
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- | 2.8304 | 15100 | 0.0009 | - |
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- | 2.8397 | 15150 | 0.0009 | - |
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- | 2.8491 | 15200 | 0.0008 | - |
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- | 2.8585 | 15250 | 0.0013 | - |
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- | 2.8679 | 15300 | 0.0011 | - |
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- | 2.8772 | 15350 | 0.0008 | - |
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- | 2.8866 | 15400 | 0.0006 | - |
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- | 2.8960 | 15450 | 0.0008 | - |
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- | 2.9053 | 15500 | 0.0009 | - |
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- | 2.9147 | 15550 | 0.0009 | - |
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- | 2.9241 | 15600 | 0.0009 | - |
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- | 2.9335 | 15650 | 0.001 | - |
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- | 2.9428 | 15700 | 0.0007 | - |
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- | 2.9522 | 15750 | 0.0012 | - |
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- | 2.9616 | 15800 | 0.0008 | - |
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- | 2.9709 | 15850 | 0.001 | - |
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- | 2.9803 | 15900 | 0.0009 | - |
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- | 2.9897 | 15950 | 0.0011 | - |
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- | 2.9991 | 16000 | 0.0005 | - |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
479
 
480
  ### Framework Versions
481
  - Python: 3.13.7
 
34
  split: test
35
  metrics:
36
  - type: micro_f1
37
+ value: 0.5631067961165048
38
  name: Micro_F1
39
  - type: macro_f1
40
+ value: 0.5741774726671751
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  name: Macro_F1
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  - type: hamming_accuracy
43
+ value: 0.8888888888888888
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  name: Hamming_Accuracy
45
  - type: subset_accuracy
46
+ value: 0.5637860082304527
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  name: Subset_Accuracy
48
  ---
49
 
 
79
  ### Metrics
80
  | Label | Micro_F1 | Macro_F1 | Hamming_Accuracy | Subset_Accuracy |
81
  |:--------|:---------|:---------|:-----------------|:----------------|
82
+ | **all** | 0.5631 | 0.5742 | 0.8889 | 0.5638 |
83
 
84
  ## Uses
85
 
 
138
  - num_epochs: (3, 3)
139
  - max_steps: -1
140
  - sampling_strategy: oversampling
141
+ - num_iterations: 200
142
  - body_learning_rate: (1e-05, 1e-05)
143
  - head_learning_rate: 1e-05
144
  - loss: CosineSimilarityLoss
 
155
  ### Training Results
156
  | Epoch | Step | Training Loss | Validation Loss |
157
  |:------:|:-----:|:-------------:|:---------------:|
158
+ | 0.0001 | 1 | 0.3722 | - |
159
+ | 0.0070 | 50 | 0.3592 | - |
160
+ | 0.0141 | 100 | 0.3552 | - |
161
+ | 0.0211 | 150 | 0.3271 | - |
162
+ | 0.0281 | 200 | 0.3016 | - |
163
+ | 0.0351 | 250 | 0.2783 | - |
164
+ | 0.0422 | 300 | 0.2642 | - |
165
+ | 0.0492 | 350 | 0.2587 | - |
166
+ | 0.0562 | 400 | 0.2568 | - |
167
+ | 0.0633 | 450 | 0.257 | - |
168
+ | 0.0703 | 500 | 0.2498 | - |
169
+ | 0.0773 | 550 | 0.2444 | - |
170
+ | 0.0844 | 600 | 0.2437 | - |
171
+ | 0.0914 | 650 | 0.2399 | - |
172
+ | 0.0984 | 700 | 0.2371 | - |
173
+ | 0.1054 | 750 | 0.2302 | - |
174
+ | 0.1125 | 800 | 0.2291 | - |
175
+ | 0.1195 | 850 | 0.2233 | - |
176
+ | 0.1265 | 900 | 0.2192 | - |
177
+ | 0.1336 | 950 | 0.2229 | - |
178
+ | 0.1406 | 1000 | 0.218 | - |
179
+ | 0.1476 | 1050 | 0.2096 | - |
180
+ | 0.1546 | 1100 | 0.2107 | - |
181
+ | 0.1617 | 1150 | 0.202 | - |
182
+ | 0.1687 | 1200 | 0.2009 | - |
183
+ | 0.1757 | 1250 | 0.1975 | - |
184
+ | 0.1828 | 1300 | 0.1969 | - |
185
+ | 0.1898 | 1350 | 0.1955 | - |
186
+ | 0.1968 | 1400 | 0.1871 | - |
187
+ | 0.2039 | 1450 | 0.1837 | - |
188
+ | 0.2109 | 1500 | 0.1732 | - |
189
+ | 0.2179 | 1550 | 0.1702 | - |
190
+ | 0.2249 | 1600 | 0.1687 | - |
191
+ | 0.2320 | 1650 | 0.16 | - |
192
+ | 0.2390 | 1700 | 0.1551 | - |
193
+ | 0.2460 | 1750 | 0.1495 | - |
194
+ | 0.2531 | 1800 | 0.1386 | - |
195
+ | 0.2601 | 1850 | 0.1339 | - |
196
+ | 0.2671 | 1900 | 0.1263 | - |
197
+ | 0.2741 | 1950 | 0.1232 | - |
198
+ | 0.2812 | 2000 | 0.1209 | - |
199
+ | 0.2882 | 2050 | 0.112 | - |
200
+ | 0.2952 | 2100 | 0.0995 | - |
201
+ | 0.3023 | 2150 | 0.0932 | - |
202
+ | 0.3093 | 2200 | 0.0869 | - |
203
+ | 0.3163 | 2250 | 0.076 | - |
204
+ | 0.3234 | 2300 | 0.0656 | - |
205
+ | 0.3304 | 2350 | 0.067 | - |
206
+ | 0.3374 | 2400 | 0.0602 | - |
207
+ | 0.3444 | 2450 | 0.0561 | - |
208
+ | 0.3515 | 2500 | 0.0532 | - |
209
+ | 0.3585 | 2550 | 0.0465 | - |
210
+ | 0.3655 | 2600 | 0.0443 | - |
211
+ | 0.3726 | 2650 | 0.0443 | - |
212
+ | 0.3796 | 2700 | 0.0435 | - |
213
+ | 0.3866 | 2750 | 0.0392 | - |
214
+ | 0.3936 | 2800 | 0.0417 | - |
215
+ | 0.4007 | 2850 | 0.0354 | - |
216
+ | 0.4077 | 2900 | 0.0379 | - |
217
+ | 0.4147 | 2950 | 0.037 | - |
218
+ | 0.4218 | 3000 | 0.0366 | - |
219
+ | 0.4288 | 3050 | 0.0328 | - |
220
+ | 0.4358 | 3100 | 0.032 | - |
221
+ | 0.4429 | 3150 | 0.027 | - |
222
+ | 0.4499 | 3200 | 0.0329 | - |
223
+ | 0.4569 | 3250 | 0.026 | - |
224
+ | 0.4639 | 3300 | 0.0284 | - |
225
+ | 0.4710 | 3350 | 0.0274 | - |
226
+ | 0.4780 | 3400 | 0.0264 | - |
227
+ | 0.4850 | 3450 | 0.0239 | - |
228
+ | 0.4921 | 3500 | 0.0256 | - |
229
+ | 0.4991 | 3550 | 0.0256 | - |
230
+ | 0.5061 | 3600 | 0.024 | - |
231
+ | 0.5131 | 3650 | 0.0223 | - |
232
+ | 0.5202 | 3700 | 0.0225 | - |
233
+ | 0.5272 | 3750 | 0.0245 | - |
234
+ | 0.5342 | 3800 | 0.0224 | - |
235
+ | 0.5413 | 3850 | 0.0226 | - |
236
+ | 0.5483 | 3900 | 0.0213 | - |
237
+ | 0.5553 | 3950 | 0.0207 | - |
238
+ | 0.5624 | 4000 | 0.0177 | - |
239
+ | 0.5694 | 4050 | 0.023 | - |
240
+ | 0.5764 | 4100 | 0.0203 | - |
241
+ | 0.5834 | 4150 | 0.0194 | - |
242
+ | 0.5905 | 4200 | 0.0183 | - |
243
+ | 0.5975 | 4250 | 0.0182 | - |
244
+ | 0.6045 | 4300 | 0.0164 | - |
245
+ | 0.6116 | 4350 | 0.0159 | - |
246
+ | 0.6186 | 4400 | 0.0147 | - |
247
+ | 0.6256 | 4450 | 0.0135 | - |
248
+ | 0.6326 | 4500 | 0.0131 | - |
249
+ | 0.6397 | 4550 | 0.0111 | - |
250
+ | 0.6467 | 4600 | 0.012 | - |
251
+ | 0.6537 | 4650 | 0.011 | - |
252
+ | 0.6608 | 4700 | 0.0119 | - |
253
+ | 0.6678 | 4750 | 0.0113 | - |
254
+ | 0.6748 | 4800 | 0.0107 | - |
255
+ | 0.6819 | 4850 | 0.0092 | - |
256
+ | 0.6889 | 4900 | 0.0097 | - |
257
+ | 0.6959 | 4950 | 0.0087 | - |
258
+ | 0.7029 | 5000 | 0.0082 | - |
259
+ | 0.7100 | 5050 | 0.01 | - |
260
+ | 0.7170 | 5100 | 0.0094 | - |
261
+ | 0.7240 | 5150 | 0.0081 | - |
262
+ | 0.7311 | 5200 | 0.0073 | - |
263
+ | 0.7381 | 5250 | 0.0069 | - |
264
+ | 0.7451 | 5300 | 0.0067 | - |
265
+ | 0.7521 | 5350 | 0.0072 | - |
266
+ | 0.7592 | 5400 | 0.0067 | - |
267
+ | 0.7662 | 5450 | 0.008 | - |
268
+ | 0.7732 | 5500 | 0.0072 | - |
269
+ | 0.7803 | 5550 | 0.0059 | - |
270
+ | 0.7873 | 5600 | 0.0059 | - |
271
+ | 0.7943 | 5650 | 0.0062 | - |
272
+ | 0.8013 | 5700 | 0.0068 | - |
273
+ | 0.8084 | 5750 | 0.0066 | - |
274
+ | 0.8154 | 5800 | 0.007 | - |
275
+ | 0.8224 | 5850 | 0.0057 | - |
276
+ | 0.8295 | 5900 | 0.0063 | - |
277
+ | 0.8365 | 5950 | 0.0062 | - |
278
+ | 0.8435 | 6000 | 0.0057 | - |
279
+ | 0.8506 | 6050 | 0.0051 | - |
280
+ | 0.8576 | 6100 | 0.0055 | - |
281
+ | 0.8646 | 6150 | 0.0046 | - |
282
+ | 0.8716 | 6200 | 0.0066 | - |
283
+ | 0.8787 | 6250 | 0.0054 | - |
284
+ | 0.8857 | 6300 | 0.004 | - |
285
+ | 0.8927 | 6350 | 0.0047 | - |
286
+ | 0.8998 | 6400 | 0.0044 | - |
287
+ | 0.9068 | 6450 | 0.004 | - |
288
+ | 0.9138 | 6500 | 0.005 | - |
289
+ | 0.9208 | 6550 | 0.0043 | - |
290
+ | 0.9279 | 6600 | 0.0039 | - |
291
+ | 0.9349 | 6650 | 0.0053 | - |
292
+ | 0.9419 | 6700 | 0.0039 | - |
293
+ | 0.9490 | 6750 | 0.0043 | - |
294
+ | 0.9560 | 6800 | 0.0045 | - |
295
+ | 0.9630 | 6850 | 0.0044 | - |
296
+ | 0.9701 | 6900 | 0.0041 | - |
297
+ | 0.9771 | 6950 | 0.0033 | - |
298
+ | 0.9841 | 7000 | 0.0031 | - |
299
+ | 0.9911 | 7050 | 0.0031 | - |
300
+ | 0.9982 | 7100 | 0.0039 | - |
301
+ | 1.0052 | 7150 | 0.0041 | - |
302
+ | 1.0122 | 7200 | 0.0026 | - |
303
+ | 1.0193 | 7250 | 0.0035 | - |
304
+ | 1.0263 | 7300 | 0.0032 | - |
305
+ | 1.0333 | 7350 | 0.0033 | - |
306
+ | 1.0403 | 7400 | 0.003 | - |
307
+ | 1.0474 | 7450 | 0.0025 | - |
308
+ | 1.0544 | 7500 | 0.0028 | - |
309
+ | 1.0614 | 7550 | 0.0027 | - |
310
+ | 1.0685 | 7600 | 0.0024 | - |
311
+ | 1.0755 | 7650 | 0.0026 | - |
312
+ | 1.0825 | 7700 | 0.0024 | - |
313
+ | 1.0896 | 7750 | 0.003 | - |
314
+ | 1.0966 | 7800 | 0.0024 | - |
315
+ | 1.1036 | 7850 | 0.0028 | - |
316
+ | 1.1106 | 7900 | 0.0023 | - |
317
+ | 1.1177 | 7950 | 0.0021 | - |
318
+ | 1.1247 | 8000 | 0.0028 | - |
319
+ | 1.1317 | 8050 | 0.0017 | - |
320
+ | 1.1388 | 8100 | 0.0022 | - |
321
+ | 1.1458 | 8150 | 0.0028 | - |
322
+ | 1.1528 | 8200 | 0.0019 | - |
323
+ | 1.1598 | 8250 | 0.002 | - |
324
+ | 1.1669 | 8300 | 0.0025 | - |
325
+ | 1.1739 | 8350 | 0.0027 | - |
326
+ | 1.1809 | 8400 | 0.0025 | - |
327
+ | 1.1880 | 8450 | 0.0018 | - |
328
+ | 1.1950 | 8500 | 0.0024 | - |
329
+ | 1.2020 | 8550 | 0.002 | - |
330
+ | 1.2091 | 8600 | 0.002 | - |
331
+ | 1.2161 | 8650 | 0.0019 | - |
332
+ | 1.2231 | 8700 | 0.0016 | - |
333
+ | 1.2301 | 8750 | 0.0018 | - |
334
+ | 1.2372 | 8800 | 0.0015 | - |
335
+ | 1.2442 | 8850 | 0.0017 | - |
336
+ | 1.2512 | 8900 | 0.0017 | - |
337
+ | 1.2583 | 8950 | 0.0019 | - |
338
+ | 1.2653 | 9000 | 0.0014 | - |
339
+ | 1.2723 | 9050 | 0.0016 | - |
340
+ | 1.2793 | 9100 | 0.0014 | - |
341
+ | 1.2864 | 9150 | 0.0017 | - |
342
+ | 1.2934 | 9200 | 0.0015 | - |
343
+ | 1.3004 | 9250 | 0.001 | - |
344
+ | 1.3075 | 9300 | 0.0017 | - |
345
+ | 1.3145 | 9350 | 0.0014 | - |
346
+ | 1.3215 | 9400 | 0.0013 | - |
347
+ | 1.3286 | 9450 | 0.0012 | - |
348
+ | 1.3356 | 9500 | 0.001 | - |
349
+ | 1.3426 | 9550 | 0.0014 | - |
350
+ | 1.3496 | 9600 | 0.0011 | - |
351
+ | 1.3567 | 9650 | 0.0012 | - |
352
+ | 1.3637 | 9700 | 0.0012 | - |
353
+ | 1.3707 | 9750 | 0.002 | - |
354
+ | 1.3778 | 9800 | 0.0012 | - |
355
+ | 1.3848 | 9850 | 0.0012 | - |
356
+ | 1.3918 | 9900 | 0.0016 | - |
357
+ | 1.3988 | 9950 | 0.0014 | - |
358
+ | 1.4059 | 10000 | 0.0011 | - |
359
+ | 1.4129 | 10050 | 0.0012 | - |
360
+ | 1.4199 | 10100 | 0.0013 | - |
361
+ | 1.4270 | 10150 | 0.0011 | - |
362
+ | 1.4340 | 10200 | 0.001 | - |
363
+ | 1.4410 | 10250 | 0.0016 | - |
364
+ | 1.4481 | 10300 | 0.0012 | - |
365
+ | 1.4551 | 10350 | 0.0012 | - |
366
+ | 1.4621 | 10400 | 0.0015 | - |
367
+ | 1.4691 | 10450 | 0.0014 | - |
368
+ | 1.4762 | 10500 | 0.0017 | - |
369
+ | 1.4832 | 10550 | 0.0019 | - |
370
+ | 1.4902 | 10600 | 0.0013 | - |
371
+ | 1.4973 | 10650 | 0.0012 | - |
372
+ | 1.5043 | 10700 | 0.0015 | - |
373
+ | 1.5113 | 10750 | 0.0012 | - |
374
+ | 1.5183 | 10800 | 0.0011 | - |
375
+ | 1.5254 | 10850 | 0.0015 | - |
376
+ | 1.5324 | 10900 | 0.001 | - |
377
+ | 1.5394 | 10950 | 0.001 | - |
378
+ | 1.5465 | 11000 | 0.0008 | - |
379
+ | 1.5535 | 11050 | 0.0014 | - |
380
+ | 1.5605 | 11100 | 0.0011 | - |
381
+ | 1.5676 | 11150 | 0.0014 | - |
382
+ | 1.5746 | 11200 | 0.0013 | - |
383
+ | 1.5816 | 11250 | 0.0008 | - |
384
+ | 1.5886 | 11300 | 0.001 | - |
385
+ | 1.5957 | 11350 | 0.0009 | - |
386
+ | 1.6027 | 11400 | 0.0014 | - |
387
+ | 1.6097 | 11450 | 0.0008 | - |
388
+ | 1.6168 | 11500 | 0.0014 | - |
389
+ | 1.6238 | 11550 | 0.0011 | - |
390
+ | 1.6308 | 11600 | 0.0015 | - |
391
+ | 1.6378 | 11650 | 0.0011 | - |
392
+ | 1.6449 | 11700 | 0.0006 | - |
393
+ | 1.6519 | 11750 | 0.0015 | - |
394
+ | 1.6589 | 11800 | 0.0015 | - |
395
+ | 1.6660 | 11850 | 0.0012 | - |
396
+ | 1.6730 | 11900 | 0.0008 | - |
397
+ | 1.6800 | 11950 | 0.0007 | - |
398
+ | 1.6871 | 12000 | 0.0011 | - |
399
+ | 1.6941 | 12050 | 0.0008 | - |
400
+ | 1.7011 | 12100 | 0.001 | - |
401
+ | 1.7081 | 12150 | 0.0008 | - |
402
+ | 1.7152 | 12200 | 0.0008 | - |
403
+ | 1.7222 | 12250 | 0.0011 | - |
404
+ | 1.7292 | 12300 | 0.0018 | - |
405
+ | 1.7363 | 12350 | 0.0007 | - |
406
+ | 1.7433 | 12400 | 0.0011 | - |
407
+ | 1.7503 | 12450 | 0.0006 | - |
408
+ | 1.7573 | 12500 | 0.0007 | - |
409
+ | 1.7644 | 12550 | 0.0012 | - |
410
+ | 1.7714 | 12600 | 0.001 | - |
411
+ | 1.7784 | 12650 | 0.0009 | - |
412
+ | 1.7855 | 12700 | 0.0009 | - |
413
+ | 1.7925 | 12750 | 0.0008 | - |
414
+ | 1.7995 | 12800 | 0.0009 | - |
415
+ | 1.8066 | 12850 | 0.0009 | - |
416
+ | 1.8136 | 12900 | 0.0013 | - |
417
+ | 1.8206 | 12950 | 0.0009 | - |
418
+ | 1.8276 | 13000 | 0.0011 | - |
419
+ | 1.8347 | 13050 | 0.0009 | - |
420
+ | 1.8417 | 13100 | 0.0007 | - |
421
+ | 1.8487 | 13150 | 0.0009 | - |
422
+ | 1.8558 | 13200 | 0.0008 | - |
423
+ | 1.8628 | 13250 | 0.0008 | - |
424
+ | 1.8698 | 13300 | 0.0006 | - |
425
+ | 1.8768 | 13350 | 0.0008 | - |
426
+ | 1.8839 | 13400 | 0.0007 | - |
427
+ | 1.8909 | 13450 | 0.0009 | - |
428
+ | 1.8979 | 13500 | 0.0005 | - |
429
+ | 1.9050 | 13550 | 0.0004 | - |
430
+ | 1.9120 | 13600 | 0.0014 | - |
431
+ | 1.9190 | 13650 | 0.0009 | - |
432
+ | 1.9261 | 13700 | 0.0009 | - |
433
+ | 1.9331 | 13750 | 0.001 | - |
434
+ | 1.9401 | 13800 | 0.0007 | - |
435
+ | 1.9471 | 13850 | 0.0011 | - |
436
+ | 1.9542 | 13900 | 0.0009 | - |
437
+ | 1.9612 | 13950 | 0.0005 | - |
438
+ | 1.9682 | 14000 | 0.0004 | - |
439
+ | 1.9753 | 14050 | 0.0007 | - |
440
+ | 1.9823 | 14100 | 0.0007 | - |
441
+ | 1.9893 | 14150 | 0.0006 | - |
442
+ | 1.9963 | 14200 | 0.0008 | - |
443
+ | 2.0034 | 14250 | 0.0005 | - |
444
+ | 2.0104 | 14300 | 0.0009 | - |
445
+ | 2.0174 | 14350 | 0.0004 | - |
446
+ | 2.0245 | 14400 | 0.0007 | - |
447
+ | 2.0315 | 14450 | 0.0007 | - |
448
+ | 2.0385 | 14500 | 0.0005 | - |
449
+ | 2.0456 | 14550 | 0.0007 | - |
450
+ | 2.0526 | 14600 | 0.0005 | - |
451
+ | 2.0596 | 14650 | 0.0004 | - |
452
+ | 2.0666 | 14700 | 0.0006 | - |
453
+ | 2.0737 | 14750 | 0.0007 | - |
454
+ | 2.0807 | 14800 | 0.0008 | - |
455
+ | 2.0877 | 14850 | 0.0009 | - |
456
+ | 2.0948 | 14900 | 0.0003 | - |
457
+ | 2.1018 | 14950 | 0.0006 | - |
458
+ | 2.1088 | 15000 | 0.0006 | - |
459
+ | 2.1158 | 15050 | 0.0007 | - |
460
+ | 2.1229 | 15100 | 0.0007 | - |
461
+ | 2.1299 | 15150 | 0.001 | - |
462
+ | 2.1369 | 15200 | 0.0006 | - |
463
+ | 2.1440 | 15250 | 0.0005 | - |
464
+ | 2.1510 | 15300 | 0.0008 | - |
465
+ | 2.1580 | 15350 | 0.0004 | - |
466
+ | 2.1650 | 15400 | 0.0006 | - |
467
+ | 2.1721 | 15450 | 0.0006 | - |
468
+ | 2.1791 | 15500 | 0.0008 | - |
469
+ | 2.1861 | 15550 | 0.0003 | - |
470
+ | 2.1932 | 15600 | 0.001 | - |
471
+ | 2.2002 | 15650 | 0.0005 | - |
472
+ | 2.2072 | 15700 | 0.0006 | - |
473
+ | 2.2143 | 15750 | 0.0005 | - |
474
+ | 2.2213 | 15800 | 0.0006 | - |
475
+ | 2.2283 | 15850 | 0.0005 | - |
476
+ | 2.2353 | 15900 | 0.0006 | - |
477
+ | 2.2424 | 15950 | 0.0003 | - |
478
+ | 2.2494 | 16000 | 0.0005 | - |
479
+ | 2.2564 | 16050 | 0.0005 | - |
480
+ | 2.2635 | 16100 | 0.0006 | - |
481
+ | 2.2705 | 16150 | 0.0006 | - |
482
+ | 2.2775 | 16200 | 0.0006 | - |
483
+ | 2.2845 | 16250 | 0.0005 | - |
484
+ | 2.2916 | 16300 | 0.0006 | - |
485
+ | 2.2986 | 16350 | 0.0004 | - |
486
+ | 2.3056 | 16400 | 0.0006 | - |
487
+ | 2.3127 | 16450 | 0.0004 | - |
488
+ | 2.3197 | 16500 | 0.0004 | - |
489
+ | 2.3267 | 16550 | 0.0007 | - |
490
+ | 2.3338 | 16600 | 0.0006 | - |
491
+ | 2.3408 | 16650 | 0.0004 | - |
492
+ | 2.3478 | 16700 | 0.0007 | - |
493
+ | 2.3548 | 16750 | 0.0009 | - |
494
+ | 2.3619 | 16800 | 0.0005 | - |
495
+ | 2.3689 | 16850 | 0.0005 | - |
496
+ | 2.3759 | 16900 | 0.0007 | - |
497
+ | 2.3830 | 16950 | 0.0005 | - |
498
+ | 2.3900 | 17000 | 0.0005 | - |
499
+ | 2.3970 | 17050 | 0.0008 | - |
500
+ | 2.4040 | 17100 | 0.0005 | - |
501
+ | 2.4111 | 17150 | 0.0004 | - |
502
+ | 2.4181 | 17200 | 0.0004 | - |
503
+ | 2.4251 | 17250 | 0.0006 | - |
504
+ | 2.4322 | 17300 | 0.0007 | - |
505
+ | 2.4392 | 17350 | 0.0005 | - |
506
+ | 2.4462 | 17400 | 0.0004 | - |
507
+ | 2.4533 | 17450 | 0.0003 | - |
508
+ | 2.4603 | 17500 | 0.0004 | - |
509
+ | 2.4673 | 17550 | 0.0008 | - |
510
+ | 2.4743 | 17600 | 0.0003 | - |
511
+ | 2.4814 | 17650 | 0.0006 | - |
512
+ | 2.4884 | 17700 | 0.0003 | - |
513
+ | 2.4954 | 17750 | 0.0004 | - |
514
+ | 2.5025 | 17800 | 0.0005 | - |
515
+ | 2.5095 | 17850 | 0.0004 | - |
516
+ | 2.5165 | 17900 | 0.0004 | - |
517
+ | 2.5235 | 17950 | 0.0003 | - |
518
+ | 2.5306 | 18000 | 0.0005 | - |
519
+ | 2.5376 | 18050 | 0.0005 | - |
520
+ | 2.5446 | 18100 | 0.0005 | - |
521
+ | 2.5517 | 18150 | 0.0004 | - |
522
+ | 2.5587 | 18200 | 0.0003 | - |
523
+ | 2.5657 | 18250 | 0.0007 | - |
524
+ | 2.5728 | 18300 | 0.0006 | - |
525
+ | 2.5798 | 18350 | 0.0004 | - |
526
+ | 2.5868 | 18400 | 0.0005 | - |
527
+ | 2.5938 | 18450 | 0.0006 | - |
528
+ | 2.6009 | 18500 | 0.0006 | - |
529
+ | 2.6079 | 18550 | 0.0006 | - |
530
+ | 2.6149 | 18600 | 0.0003 | - |
531
+ | 2.6220 | 18650 | 0.0003 | - |
532
+ | 2.6290 | 18700 | 0.0003 | - |
533
+ | 2.6360 | 18750 | 0.0004 | - |
534
+ | 2.6430 | 18800 | 0.0003 | - |
535
+ | 2.6501 | 18850 | 0.0005 | - |
536
+ | 2.6571 | 18900 | 0.0006 | - |
537
+ | 2.6641 | 18950 | 0.0003 | - |
538
+ | 2.6712 | 19000 | 0.0007 | - |
539
+ | 2.6782 | 19050 | 0.0002 | - |
540
+ | 2.6852 | 19100 | 0.0003 | - |
541
+ | 2.6923 | 19150 | 0.0004 | - |
542
+ | 2.6993 | 19200 | 0.0005 | - |
543
+ | 2.7063 | 19250 | 0.0004 | - |
544
+ | 2.7133 | 19300 | 0.0004 | - |
545
+ | 2.7204 | 19350 | 0.0006 | - |
546
+ | 2.7274 | 19400 | 0.0003 | - |
547
+ | 2.7344 | 19450 | 0.0002 | - |
548
+ | 2.7415 | 19500 | 0.0003 | - |
549
+ | 2.7485 | 19550 | 0.0004 | - |
550
+ | 2.7555 | 19600 | 0.0005 | - |
551
+ | 2.7625 | 19650 | 0.0004 | - |
552
+ | 2.7696 | 19700 | 0.0007 | - |
553
+ | 2.7766 | 19750 | 0.0003 | - |
554
+ | 2.7836 | 19800 | 0.0004 | - |
555
+ | 2.7907 | 19850 | 0.0006 | - |
556
+ | 2.7977 | 19900 | 0.0005 | - |
557
+ | 2.8047 | 19950 | 0.0004 | - |
558
+ | 2.8118 | 20000 | 0.0003 | - |
559
+ | 2.8188 | 20050 | 0.0007 | - |
560
+ | 2.8258 | 20100 | 0.0005 | - |
561
+ | 2.8328 | 20150 | 0.0006 | - |
562
+ | 2.8399 | 20200 | 0.0003 | - |
563
+ | 2.8469 | 20250 | 0.0008 | - |
564
+ | 2.8539 | 20300 | 0.0004 | - |
565
+ | 2.8610 | 20350 | 0.0007 | - |
566
+ | 2.8680 | 20400 | 0.0003 | - |
567
+ | 2.8750 | 20450 | 0.0005 | - |
568
+ | 2.8820 | 20500 | 0.0006 | - |
569
+ | 2.8891 | 20550 | 0.0002 | - |
570
+ | 2.8961 | 20600 | 0.0003 | - |
571
+ | 2.9031 | 20650 | 0.0004 | - |
572
+ | 2.9102 | 20700 | 0.0003 | - |
573
+ | 2.9172 | 20750 | 0.0004 | - |
574
+ | 2.9242 | 20800 | 0.0002 | - |
575
+ | 2.9313 | 20850 | 0.0003 | - |
576
+ | 2.9383 | 20900 | 0.0004 | - |
577
+ | 2.9453 | 20950 | 0.0005 | - |
578
+ | 2.9523 | 21000 | 0.0003 | - |
579
+ | 2.9594 | 21050 | 0.0005 | - |
580
+ | 2.9664 | 21100 | 0.0006 | - |
581
+ | 2.9734 | 21150 | 0.0003 | - |
582
+ | 2.9805 | 21200 | 0.0005 | - |
583
+ | 2.9875 | 21250 | 0.0003 | - |
584
+ | 2.9945 | 21300 | 0.0003 | - |
585
 
586
  ### Framework Versions
587
  - Python: 3.13.7
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