End of training
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README.md
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Classification Report: {'0': {'precision': 0.
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Classification Report
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| No log | 1.0 | 9 | 0.
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| No log | 2.0 | 18 | 0.
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| No log | 3.0 | 27 | 0.
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| No log | 4.0 | 36 | 0.
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| No log | 5.0 | 45 | 0.
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| No log | 6.0 | 54 | 0.
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| No log | 7.0 | 63 | 0.
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| No log | 8.0 | 72 | 0.
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| No log | 9.0 | 81 | 0.
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| No log | 10.0 | 90 | 0.
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| No log | 11.0 | 99 | 0.
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| No log | 12.0 | 108 | 0.
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| No log | 13.0 | 117 | 0.
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| No log | 14.0 | 126 | 0.
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| No log | 15.0 | 135 | 0.
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| No log | 16.0 | 144 | 0.
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| No log | 17.0 | 153 | 0.
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| No log | 18.0 | 162 | 0.
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| No log | 19.0 | 171 | 0.
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| No log | 20.0 | 180 | 0.
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| No log | 21.0 | 189 | 0.
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| No log | 22.0 | 198 | 0.
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| No log | 23.0 | 207 | 0.
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| 78 |
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| No log | 24.0 | 216 | 0.
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| No log | 25.0 | 225 | 0.
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| No log | 26.0 | 234 | 0.
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| No log | 27.0 | 243 | 0.
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| No log | 28.0 | 252 | 0.
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| 83 |
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| No log | 29.0 | 261 | 0.
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| No log | 30.0 | 270 | 0.
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| 85 |
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| No log | 31.0 | 279 | 0.
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| No log | 32.0 | 288 | 0.
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| 87 |
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| No log | 33.0 | 297 | 0.
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| 88 |
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| No log | 34.0 | 306 | 0.
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| No log | 35.0 | 315 | 0.
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| No log | 36.0 | 324 | 0.
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| No log | 37.0 | 333 | 0.
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| No log | 38.0 | 342 | 0.
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| No log | 39.0 | 351 | 0.
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| No log | 40.0 | 360 | 0.
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| No log | 41.0 | 369 | 0.
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| No log | 42.0 | 378 | 0.
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| No log | 43.0 | 387 | 0.
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| No log | 44.0 | 396 | 0.
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| No log | 45.0 | 405 | 0.
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| No log | 46.0 | 414 | 0.
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| No log | 47.0 | 423 | 0.
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| No log | 48.0 | 432 | 0.
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| No log | 49.0 | 441 | 0.
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| No log | 50.0 | 450 | 0.
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### Framework versions
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9245
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- Classification Report: {'0': {'precision': 0.9460297766749379, 'recall': 0.9579145728643216, 'f1-score': 0.9519350811485643, 'support': 1592.0}, '1': {'precision': 0.7208333333333333, 'recall': 0.6653846153846154, 'f1-score': 0.692, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8334315550041356, 'recall': 0.8116495941244685, 'f1-score': 0.8219675405742821, 'support': 1852.0}, 'weighted avg': {'precision': 0.914414725233892, 'recall': 0.9168466522678186, 'f1-score': 0.9154431151125887, 'support': 1852.0}}
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Classification Report |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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| No log | 1.0 | 9 | 0.4849 | {'0': {'precision': 0.9859307359307359, 'recall': 0.5722361809045227, 'f1-score': 0.7241653418124007, 'support': 1592.0}, '1': {'precision': 0.2661637931034483, 'recall': 0.95, 'f1-score': 0.4158249158249158, 'support': 260.0}, 'accuracy': 0.6252699784017278, 'macro avg': {'precision': 0.626047264517092, 'recall': 0.7611180904522613, 'f1-score': 0.5699951288186582, 'support': 1852.0}, 'weighted avg': {'precision': 0.8848835409333844, 'recall': 0.6252699784017278, 'f1-score': 0.6808778090063822, 'support': 1852.0}} |
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| No log | 2.0 | 18 | 0.4361 | {'0': {'precision': 0.9823874755381604, 'recall': 0.6306532663316583, 'f1-score': 0.7681713848508034, 'support': 1592.0}, '1': {'precision': 0.29156626506024097, 'recall': 0.9307692307692308, 'f1-score': 0.44403669724770645, 'support': 260.0}, 'accuracy': 0.6727861771058316, 'macro avg': {'precision': 0.6369768702992007, 'recall': 0.7807112485504446, 'f1-score': 0.6061040410492549, 'support': 1852.0}, 'weighted avg': {'precision': 0.8854039362702019, 'recall': 0.6727861771058316, 'f1-score': 0.7226665151009085, 'support': 1852.0}} |
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| No log | 3.0 | 27 | 0.4038 | {'0': {'precision': 0.9841129744042365, 'recall': 0.7003768844221105, 'f1-score': 0.818348623853211, 'support': 1592.0}, '1': {'precision': 0.33657858136300417, 'recall': 0.9307692307692308, 'f1-score': 0.4943820224719101, 'support': 260.0}, 'accuracy': 0.7327213822894169, 'macro avg': {'precision': 0.6603457778836204, 'recall': 0.8155730575956707, 'f1-score': 0.6563653231625606, 'support': 1852.0}, 'weighted avg': {'precision': 0.8932064181457481, 'recall': 0.7327213822894169, 'f1-score': 0.7728673515210629, 'support': 1852.0}} |
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| No log | 4.0 | 36 | 0.3820 | {'0': {'precision': 0.9833194328607172, 'recall': 0.7405778894472361, 'f1-score': 0.8448584736653529, 'support': 1592.0}, '1': {'precision': 0.3675344563552833, 'recall': 0.9230769230769231, 'f1-score': 0.5257393209200438, 'support': 260.0}, 'accuracy': 0.7661987041036717, 'macro avg': {'precision': 0.6754269446080002, 'recall': 0.8318274062620796, 'f1-score': 0.6852988972926983, 'support': 1852.0}, 'weighted avg': {'precision': 0.8968701381029348, 'recall': 0.7661987041036717, 'f1-score': 0.8000577286795103, 'support': 1852.0}} |
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| No log | 5.0 | 45 | 0.3735 | {'0': {'precision': 0.9657631954350927, 'recall': 0.8505025125628141, 'f1-score': 0.9044756179024717, 'support': 1592.0}, '1': {'precision': 0.4711111111111111, 'recall': 0.8153846153846154, 'f1-score': 0.5971830985915493, 'support': 260.0}, 'accuracy': 0.8455723542116631, 'macro avg': {'precision': 0.7184371532731019, 'recall': 0.8329435639737147, 'f1-score': 0.7508293582470105, 'support': 1852.0}, 'weighted avg': {'precision': 0.8963195982837777, 'recall': 0.8455723542116631, 'f1-score': 0.8613351994246963, 'support': 1852.0}} |
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| No log | 6.0 | 54 | 0.3759 | {'0': {'precision': 0.9601620526671168, 'recall': 0.8932160804020101, 'f1-score': 0.9254799869834038, 'support': 1592.0}, '1': {'precision': 0.5417789757412399, 'recall': 0.7730769230769231, 'f1-score': 0.6370839936608558, 'support': 260.0}, 'accuracy': 0.8763498920086393, 'macro avg': {'precision': 0.7509705142041784, 'recall': 0.8331465017394666, 'f1-score': 0.7812819903221297, 'support': 1852.0}, 'weighted avg': {'precision': 0.9014257675695315, 'recall': 0.8763498920086393, 'f1-score': 0.8849924285255948, 'support': 1852.0}} |
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| No log | 7.0 | 63 | 0.3701 | {'0': {'precision': 0.9560943643512451, 'recall': 0.9164572864321608, 'f1-score': 0.935856318152662, 'support': 1592.0}, '1': {'precision': 0.5920245398773006, 'recall': 0.7423076923076923, 'f1-score': 0.658703071672355, 'support': 260.0}, 'accuracy': 0.8920086393088553, 'macro avg': {'precision': 0.7740594521142729, 'recall': 0.8293824893699266, 'f1-score': 0.7972796949125085, 'support': 1852.0}, 'weighted avg': {'precision': 0.9049830499002592, 'recall': 0.8920086393088553, 'f1-score': 0.8969471150830725, 'support': 1852.0}} |
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| No log | 8.0 | 72 | 0.3211 | {'0': {'precision': 0.9728765167737331, 'recall': 0.8561557788944724, 'f1-score': 0.9107918476445038, 'support': 1592.0}, '1': {'precision': 0.49223946784922396, 'recall': 0.8538461538461538, 'f1-score': 0.6244725738396625, 'support': 260.0}, 'accuracy': 0.8558315334773218, 'macro avg': {'precision': 0.7325579923114786, 'recall': 0.8550009663703131, 'f1-score': 0.7676322107420832, 'support': 1852.0}, 'weighted avg': {'precision': 0.9054004731882189, 'recall': 0.8558315334773218, 'f1-score': 0.8705958372831331, 'support': 1852.0}} |
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| No log | 9.0 | 81 | 0.3262 | {'0': {'precision': 0.9895245769540693, 'recall': 0.7713567839195979, 'f1-score': 0.8669255206494881, 'support': 1592.0}, '1': {'precision': 0.40425531914893614, 'recall': 0.95, 'f1-score': 0.5671641791044776, 'support': 260.0}, 'accuracy': 0.7964362850971922, 'macro avg': {'precision': 0.6968899480515027, 'recall': 0.8606783919597989, 'f1-score': 0.7170448498769828, 'support': 1852.0}, 'weighted avg': {'precision': 0.9073593463766747, 'recall': 0.7964362850971922, 'f1-score': 0.8248423949466249, 'support': 1852.0}} |
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| No log | 10.0 | 90 | 0.3277 | {'0': {'precision': 0.965893587994543, 'recall': 0.8894472361809045, 'f1-score': 0.9260954872465664, 'support': 1592.0}, '1': {'precision': 0.5440414507772021, 'recall': 0.8076923076923077, 'f1-score': 0.6501547987616099, 'support': 260.0}, 'accuracy': 0.8779697624190065, 'macro avg': {'precision': 0.7549675193858725, 'recall': 0.8485697719366061, 'f1-score': 0.7881251430040881, 'support': 1852.0}, 'weighted avg': {'precision': 0.9066702857934043, 'recall': 0.8779697624190065, 'f1-score': 0.8873565137011622, 'support': 1852.0}} |
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| No log | 11.0 | 99 | 0.3093 | {'0': {'precision': 0.9893048128342246, 'recall': 0.8134422110552764, 'f1-score': 0.8927955877283695, 'support': 1592.0}, '1': {'precision': 0.4530386740331492, 'recall': 0.9461538461538461, 'f1-score': 0.6127023661270237, 'support': 260.0}, 'accuracy': 0.83207343412527, 'macro avg': {'precision': 0.7211717434336868, 'recall': 0.8797980286045612, 'f1-score': 0.7527489769276966, 'support': 1852.0}, 'weighted avg': {'precision': 0.9140190698059959, 'recall': 0.83207343412527, 'f1-score': 0.8534736451709453, 'support': 1852.0}} |
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| No log | 12.0 | 108 | 0.3208 | {'0': {'precision': 0.9661705006765899, 'recall': 0.8969849246231156, 'f1-score': 0.9302931596091205, 'support': 1592.0}, '1': {'precision': 0.5614973262032086, 'recall': 0.8076923076923077, 'f1-score': 0.6624605678233438, 'support': 260.0}, 'accuracy': 0.8844492440604752, 'macro avg': {'precision': 0.7638339134398993, 'recall': 0.8523386161577117, 'f1-score': 0.7963768637162322, 'support': 1852.0}, 'weighted avg': {'precision': 0.9093589319060289, 'recall': 0.8844492440604752, 'f1-score': 0.892692471777424, 'support': 1852.0}} |
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| No log | 13.0 | 117 | 0.3203 | {'0': {'precision': 0.9624505928853755, 'recall': 0.917713567839196, 'f1-score': 0.9395498392282958, 'support': 1592.0}, '1': {'precision': 0.6077844311377245, 'recall': 0.7807692307692308, 'f1-score': 0.6835016835016835, 'support': 260.0}, 'accuracy': 0.8984881209503239, 'macro avg': {'precision': 0.78511751201155, 'recall': 0.8492413993042134, 'f1-score': 0.8115257613649897, 'support': 1852.0}, 'weighted avg': {'precision': 0.9126594470676708, 'recall': 0.8984881209503239, 'f1-score': 0.9036035538671083, 'support': 1852.0}} |
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| No log | 14.0 | 126 | 0.2882 | {'0': {'precision': 0.9829755736491488, 'recall': 0.8341708542713567, 'f1-score': 0.9024804621134896, 'support': 1592.0}, '1': {'precision': 0.47305389221556887, 'recall': 0.9115384615384615, 'f1-score': 0.6228646517739816, 'support': 260.0}, 'accuracy': 0.8450323974082073, 'macro avg': {'precision': 0.7280147329323589, 'recall': 0.8728546579049091, 'f1-score': 0.7626725569437356, 'support': 1852.0}, 'weighted avg': {'precision': 0.9113882965580414, 'recall': 0.8450323974082073, 'f1-score': 0.863225542735373, 'support': 1852.0}} |
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| No log | 15.0 | 135 | 0.2910 | {'0': {'precision': 0.9804347826086957, 'recall': 0.8498743718592965, 'f1-score': 0.9104979811574697, 'support': 1592.0}, '1': {'precision': 0.4936440677966102, 'recall': 0.8961538461538462, 'f1-score': 0.6366120218579235, 'support': 260.0}, 'accuracy': 0.8563714902807775, 'macro avg': {'precision': 0.7370394252026529, 'recall': 0.8730141090065713, 'f1-score': 0.7735550015076966, 'support': 1852.0}, 'weighted avg': {'precision': 0.9120948334450121, 'recall': 0.8563714902807775, 'f1-score': 0.872047468512825, 'support': 1852.0}} |
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| No log | 16.0 | 144 | 0.3558 | {'0': {'precision': 0.9601286173633441, 'recall': 0.9378140703517588, 'f1-score': 0.9488401652367334, 'support': 1592.0}, '1': {'precision': 0.6666666666666666, 'recall': 0.7615384615384615, 'f1-score': 0.7109515260323159, 'support': 260.0}, 'accuracy': 0.9130669546436285, 'macro avg': {'precision': 0.8133976420150053, 'recall': 0.8496762659451101, 'f1-score': 0.8298958456345247, 'support': 1852.0}, 'weighted avg': {'precision': 0.9189298553864887, 'recall': 0.9130669546436285, 'f1-score': 0.9154432720438886, 'support': 1852.0}} |
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| No log | 17.0 | 153 | 0.2957 | {'0': {'precision': 0.9756969263759828, 'recall': 0.8574120603015075, 'f1-score': 0.9127382146439318, 'support': 1592.0}, '1': {'precision': 0.4988962472406181, 'recall': 0.8692307692307693, 'f1-score': 0.6339410939691444, 'support': 260.0}, 'accuracy': 0.8590712742980562, 'macro avg': {'precision': 0.7372965868083005, 'recall': 0.8633214147661383, 'f1-score': 0.7733396543065381, 'support': 1852.0}, 'weighted avg': {'precision': 0.9087594660222059, 'recall': 0.8590712742980562, 'f1-score': 0.8735982300999553, 'support': 1852.0}} |
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| No log | 18.0 | 162 | 0.3945 | {'0': {'precision': 0.9550063371356147, 'recall': 0.946608040201005, 'f1-score': 0.950788643533123, 'support': 1592.0}, '1': {'precision': 0.6897810218978102, 'recall': 0.7269230769230769, 'f1-score': 0.7078651685393258, 'support': 260.0}, 'accuracy': 0.9157667386609071, 'macro avg': {'precision': 0.8223936795167124, 'recall': 0.8367655585620409, 'f1-score': 0.8293269060362244, 'support': 1852.0}, 'weighted avg': {'precision': 0.9177716816486658, 'recall': 0.9157667386609071, 'f1-score': 0.9166849159422011, 'support': 1852.0}} |
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| No log | 19.0 | 171 | 0.3045 | {'0': {'precision': 0.9774545454545455, 'recall': 0.8442211055276382, 'f1-score': 0.9059656218402427, 'support': 1592.0}, '1': {'precision': 0.480083857442348, 'recall': 0.8807692307692307, 'f1-score': 0.621438263229308, 'support': 260.0}, 'accuracy': 0.8493520518358532, 'macro avg': {'precision': 0.7287692014484467, 'recall': 0.8624951681484345, 'f1-score': 0.7637019425347753, 'support': 1852.0}, 'weighted avg': {'precision': 0.9076292868783191, 'recall': 0.8493520518358532, 'f1-score': 0.866021176246915, 'support': 1852.0}} |
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| No log | 20.0 | 180 | 0.4851 | {'0': {'precision': 0.9439309919901417, 'recall': 0.9623115577889447, 'f1-score': 0.9530326594090203, 'support': 1592.0}, '1': {'precision': 0.7379912663755459, 'recall': 0.65, 'f1-score': 0.6912065439672802, 'support': 260.0}, 'accuracy': 0.9184665226781857, 'macro avg': {'precision': 0.8409611291828438, 'recall': 0.8061557788944724, 'f1-score': 0.8221196016881502, 'support': 1852.0}, 'weighted avg': {'precision': 0.9150193674438163, 'recall': 0.9184665226781857, 'f1-score': 0.9162752133966809, 'support': 1852.0}} |
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| No log | 21.0 | 189 | 0.3723 | {'0': {'precision': 0.9577464788732394, 'recall': 0.9396984924623115, 'f1-score': 0.9486366518706405, 'support': 1592.0}, '1': {'precision': 0.6689655172413793, 'recall': 0.7461538461538462, 'f1-score': 0.7054545454545454, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.8133559980573093, 'recall': 0.8429261693080788, 'f1-score': 0.827045598662593, 'support': 1852.0}, 'weighted avg': {'precision': 0.917204875188421, 'recall': 0.9125269978401728, 'f1-score': 0.9144966153327438, 'support': 1852.0}} |
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| No log | 22.0 | 198 | 0.3060 | {'0': {'precision': 0.9784637473079684, 'recall': 0.8561557788944724, 'f1-score': 0.9132328308207706, 'support': 1592.0}, '1': {'precision': 0.5010893246187363, 'recall': 0.8846153846153846, 'f1-score': 0.6397774687065368, 'support': 260.0}, 'accuracy': 0.8601511879049676, 'macro avg': {'precision': 0.7397765359633524, 'recall': 0.8703855817549284, 'f1-score': 0.7765051497636537, 'support': 1852.0}, 'weighted avg': {'precision': 0.9114457398030005, 'recall': 0.8601511879049676, 'f1-score': 0.874842769184863, 'support': 1852.0}} |
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| No log | 23.0 | 207 | 0.3078 | {'0': {'precision': 0.9812409812409812, 'recall': 0.8542713567839196, 'f1-score': 0.9133646742780389, 'support': 1592.0}, '1': {'precision': 0.5021459227467812, 'recall': 0.9, 'f1-score': 0.6446280991735537, 'support': 260.0}, 'accuracy': 0.8606911447084233, 'macro avg': {'precision': 0.7416934519938811, 'recall': 0.8771356783919598, 'f1-score': 0.7789963867257963, 'support': 1852.0}, 'weighted avg': {'precision': 0.9139814157936315, 'recall': 0.8606911447084233, 'f1-score': 0.8756370773411241, 'support': 1852.0}} |
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| 78 |
+
| No log | 24.0 | 216 | 0.3077 | {'0': {'precision': 0.9831748354059985, 'recall': 0.8442211055276382, 'f1-score': 0.9084150050692802, 'support': 1592.0}, '1': {'precision': 0.488659793814433, 'recall': 0.9115384615384615, 'f1-score': 0.636241610738255, 'support': 260.0}, 'accuracy': 0.853671706263499, 'macro avg': {'precision': 0.7359173146102157, 'recall': 0.8778797835330499, 'f1-score': 0.7723283079037676, 'support': 1852.0}, 'weighted avg': {'precision': 0.9137504775151739, 'recall': 0.853671706263499, 'f1-score': 0.8702049173122249, 'support': 1852.0}} |
|
| 79 |
+
| No log | 25.0 | 225 | 0.3860 | {'0': {'precision': 0.9623376623376624, 'recall': 0.9309045226130653, 'f1-score': 0.946360153256705, 'support': 1592.0}, '1': {'precision': 0.6474358974358975, 'recall': 0.7769230769230769, 'f1-score': 0.7062937062937062, 'support': 260.0}, 'accuracy': 0.9092872570194385, 'macro avg': {'precision': 0.8048867798867799, 'recall': 0.8539137997680711, 'f1-score': 0.8263269297752056, 'support': 1852.0}, 'weighted avg': {'precision': 0.9181289912391424, 'recall': 0.9092872570194385, 'f1-score': 0.9126575203137355, 'support': 1852.0}} |
|
| 80 |
+
| No log | 26.0 | 234 | 0.3761 | {'0': {'precision': 0.9669749009247027, 'recall': 0.9195979899497487, 'f1-score': 0.9426915647134578, 'support': 1592.0}, '1': {'precision': 0.621301775147929, 'recall': 0.8076923076923077, 'f1-score': 0.7023411371237458, 'support': 260.0}, 'accuracy': 0.9038876889848813, 'macro avg': {'precision': 0.7941383380363158, 'recall': 0.8636451488210282, 'f1-score': 0.8225163509186018, 'support': 1852.0}, 'weighted avg': {'precision': 0.9184462763556092, 'recall': 0.9038876889848813, 'f1-score': 0.908949064079913, 'support': 1852.0}} |
|
| 81 |
+
| No log | 27.0 | 243 | 0.4425 | {'0': {'precision': 0.9631067961165048, 'recall': 0.9346733668341709, 'f1-score': 0.9486770800127511, 'support': 1592.0}, '1': {'precision': 0.6612377850162866, 'recall': 0.7807692307692308, 'f1-score': 0.7160493827160493, 'support': 260.0}, 'accuracy': 0.9130669546436285, 'macro avg': {'precision': 0.8121722905663957, 'recall': 0.8577212988017009, 'f1-score': 0.8323632313644003, 'support': 1852.0}, 'weighted avg': {'precision': 0.9207277772795411, 'recall': 0.9130669546436285, 'f1-score': 0.916018763977577, 'support': 1852.0}} |
|
| 82 |
+
| No log | 28.0 | 252 | 0.4524 | {'0': {'precision': 0.9589480436177037, 'recall': 0.9390703517587939, 'f1-score': 0.948905109489051, 'support': 1592.0}, '1': {'precision': 0.6689419795221843, 'recall': 0.7538461538461538, 'f1-score': 0.7088607594936709, 'support': 260.0}, 'accuracy': 0.9130669546436285, 'macro avg': {'precision': 0.813945011569944, 'recall': 0.8464582528024739, 'f1-score': 0.828882934491361, 'support': 1852.0}, 'weighted avg': {'precision': 0.9182344493062377, 'recall': 0.9130669546436285, 'f1-score': 0.9152055787121617, 'support': 1852.0}} |
|
| 83 |
+
| No log | 29.0 | 261 | 0.4141 | {'0': {'precision': 0.9653333333333334, 'recall': 0.9095477386934674, 'f1-score': 0.9366106080206986, 'support': 1592.0}, '1': {'precision': 0.5909090909090909, 'recall': 0.8, 'f1-score': 0.6797385620915033, 'support': 260.0}, 'accuracy': 0.8941684665226782, 'macro avg': {'precision': 0.7781212121212122, 'recall': 0.8547738693467337, 'f1-score': 0.808174585056101, 'support': 1852.0}, 'weighted avg': {'precision': 0.9127683748936449, 'recall': 0.8941684665226782, 'f1-score': 0.900548657728263, 'support': 1852.0}} |
|
| 84 |
+
| No log | 30.0 | 270 | 0.5343 | {'0': {'precision': 0.9495586380832283, 'recall': 0.9459798994974874, 'f1-score': 0.9477658904971681, 'support': 1592.0}, '1': {'precision': 0.6766917293233082, 'recall': 0.6923076923076923, 'f1-score': 0.6844106463878327, 'support': 260.0}, 'accuracy': 0.9103671706263499, 'macro avg': {'precision': 0.8131251837032683, 'recall': 0.8191437959025898, 'f1-score': 0.8160882684425004, 'support': 1852.0}, 'weighted avg': {'precision': 0.911251188689287, 'recall': 0.9103671706263499, 'f1-score': 0.9107937719936977, 'support': 1852.0}} |
|
| 85 |
+
| No log | 31.0 | 279 | 0.6099 | {'0': {'precision': 0.9440298507462687, 'recall': 0.9535175879396985, 'f1-score': 0.94875, 'support': 1592.0}, '1': {'precision': 0.6967213114754098, 'recall': 0.6538461538461539, 'f1-score': 0.6746031746031746, 'support': 260.0}, 'accuracy': 0.9114470842332614, 'macro avg': {'precision': 0.8203755811108393, 'recall': 0.8036818708929262, 'f1-score': 0.8116765873015873, 'support': 1852.0}, 'weighted avg': {'precision': 0.9093105093799495, 'recall': 0.9114470842332614, 'f1-score': 0.9102628646851109, 'support': 1852.0}} |
|
| 86 |
+
| No log | 32.0 | 288 | 0.5094 | {'0': {'precision': 0.9592760180995475, 'recall': 0.9321608040201005, 'f1-score': 0.9455240522459382, 'support': 1592.0}, '1': {'precision': 0.6459016393442623, 'recall': 0.7576923076923077, 'f1-score': 0.6973451327433628, 'support': 260.0}, 'accuracy': 0.9076673866090713, 'macro avg': {'precision': 0.802588828721905, 'recall': 0.844926555856204, 'f1-score': 0.8214345924946505, 'support': 1852.0}, 'weighted avg': {'precision': 0.9152817748617647, 'recall': 0.9076673866090713, 'f1-score': 0.9106825192704147, 'support': 1852.0}} |
|
| 87 |
+
| No log | 33.0 | 297 | 0.7074 | {'0': {'precision': 0.9423666462293072, 'recall': 0.9654522613065326, 'f1-score': 0.9537697797083463, 'support': 1592.0}, '1': {'precision': 0.751131221719457, 'recall': 0.6384615384615384, 'f1-score': 0.6902286902286903, 'support': 260.0}, 'accuracy': 0.9195464362850972, 'macro avg': {'precision': 0.8467489339743821, 'recall': 0.8019568998840355, 'f1-score': 0.8219992349685183, 'support': 1852.0}, 'weighted avg': {'precision': 0.9155193404125896, 'recall': 0.9195464362850972, 'f1-score': 0.916771570602131, 'support': 1852.0}} |
|
| 88 |
+
| No log | 34.0 | 306 | 0.5431 | {'0': {'precision': 0.9587894397939472, 'recall': 0.9353015075376885, 'f1-score': 0.946899841017488, 'support': 1592.0}, '1': {'precision': 0.6555183946488294, 'recall': 0.7538461538461538, 'f1-score': 0.7012522361359571, 'support': 260.0}, 'accuracy': 0.9098272138228942, 'macro avg': {'precision': 0.8071539172213883, 'recall': 0.8445738306919212, 'f1-score': 0.8240760385767225, 'support': 1852.0}, 'weighted avg': {'precision': 0.9162135911234663, 'recall': 0.9098272138228942, 'f1-score': 0.9124136761853077, 'support': 1852.0}} |
|
| 89 |
+
| No log | 35.0 | 315 | 0.7273 | {'0': {'precision': 0.9405637254901961, 'recall': 0.9641959798994975, 'f1-score': 0.9522332506203474, 'support': 1592.0}, '1': {'precision': 0.740909090909091, 'recall': 0.6269230769230769, 'f1-score': 0.6791666666666667, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8407364081996436, 'recall': 0.7955595284112872, 'f1-score': 0.815699958643507, 'support': 1852.0}, 'weighted avg': {'precision': 0.9125344571364772, 'recall': 0.9168466522678186, 'f1-score': 0.9138977690717744, 'support': 1852.0}} |
|
| 90 |
+
| No log | 36.0 | 324 | 0.7356 | {'0': {'precision': 0.9427692307692308, 'recall': 0.9623115577889447, 'f1-score': 0.9524401616412806, 'support': 1592.0}, '1': {'precision': 0.73568281938326, 'recall': 0.6423076923076924, 'f1-score': 0.6858316221765913, 'support': 260.0}, 'accuracy': 0.9173866090712743, 'macro avg': {'precision': 0.8392260250762453, 'recall': 0.8023096250483186, 'f1-score': 0.819135891908936, 'support': 1852.0}, 'weighted avg': {'precision': 0.9136966244191485, 'recall': 0.9173866090712743, 'f1-score': 0.915011317008009, 'support': 1852.0}} |
|
| 91 |
+
| No log | 37.0 | 333 | 0.7737 | {'0': {'precision': 0.9443757725587144, 'recall': 0.9597989949748744, 'f1-score': 0.9520249221183801, 'support': 1592.0}, '1': {'precision': 0.7264957264957265, 'recall': 0.6538461538461539, 'f1-score': 0.6882591093117408, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8354357495272204, 'recall': 0.8068225744105142, 'f1-score': 0.8201420157150605, 'support': 1852.0}, 'weighted avg': {'precision': 0.9137878611243857, 'recall': 0.9168466522678186, 'f1-score': 0.914995164380947, 'support': 1852.0}} |
|
| 92 |
+
| No log | 38.0 | 342 | 0.7866 | {'0': {'precision': 0.9444444444444444, 'recall': 0.9610552763819096, 'f1-score': 0.9526774595267746, 'support': 1592.0}, '1': {'precision': 0.7327586206896551, 'recall': 0.6538461538461539, 'f1-score': 0.6910569105691057, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8386015325670497, 'recall': 0.8074507151140318, 'f1-score': 0.8218671850479402, 'support': 1852.0}, 'weighted avg': {'precision': 0.9147261322542473, 'recall': 0.91792656587473, 'f1-score': 0.9159488727400609, 'support': 1852.0}} |
|
| 93 |
+
| No log | 39.0 | 351 | 0.7593 | {'0': {'precision': 0.9475982532751092, 'recall': 0.9541457286432161, 'f1-score': 0.9508607198748044, 'support': 1592.0}, '1': {'precision': 0.7068273092369478, 'recall': 0.676923076923077, 'f1-score': 0.6915520628683693, 'support': 260.0}, 'accuracy': 0.9152267818574514, 'macro avg': {'precision': 0.8272127812560285, 'recall': 0.8155344027831466, 'f1-score': 0.8212063913715868, 'support': 1852.0}, 'weighted avg': {'precision': 0.913796716855065, 'recall': 0.9152267818574514, 'f1-score': 0.9144566967529507, 'support': 1852.0}} |
|
| 94 |
+
| No log | 40.0 | 360 | 0.9098 | {'0': {'precision': 0.9388753056234719, 'recall': 0.964824120603015, 'f1-score': 0.9516728624535316, 'support': 1592.0}, '1': {'precision': 0.7407407407407407, 'recall': 0.6153846153846154, 'f1-score': 0.6722689075630253, 'support': 260.0}, 'accuracy': 0.9157667386609071, 'macro avg': {'precision': 0.8398080231821063, 'recall': 0.7901043679938152, 'f1-score': 0.8119708850082784, 'support': 1852.0}, 'weighted avg': {'precision': 0.9110594379833475, 'recall': 0.9157667386609071, 'f1-score': 0.9124476852010847, 'support': 1852.0}} |
|
| 95 |
+
| No log | 41.0 | 369 | 0.9334 | {'0': {'precision': 0.9394495412844037, 'recall': 0.964824120603015, 'f1-score': 0.951967771924388, 'support': 1592.0}, '1': {'precision': 0.7419354838709677, 'recall': 0.6192307692307693, 'f1-score': 0.6750524109014675, 'support': 260.0}, 'accuracy': 0.9163066954643628, 'macro avg': {'precision': 0.8406925125776857, 'recall': 0.7920274449168921, 'f1-score': 0.8135100914129277, 'support': 1852.0}, 'weighted avg': {'precision': 0.9117207859239862, 'recall': 0.9163066954643628, 'f1-score': 0.9130919653012998, 'support': 1852.0}} |
|
| 96 |
+
| No log | 42.0 | 378 | 0.8437 | {'0': {'precision': 0.9465838509316771, 'recall': 0.957286432160804, 'f1-score': 0.9519050593379138, 'support': 1592.0}, '1': {'precision': 0.71900826446281, 'recall': 0.6692307692307692, 'f1-score': 0.6932270916334662, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8327960576972435, 'recall': 0.8132586006957866, 'f1-score': 0.82256607548569, 'support': 1852.0}, 'weighted avg': {'precision': 0.9146347945159614, 'recall': 0.9168466522678186, 'f1-score': 0.9155895779107236, 'support': 1852.0}} |
|
| 97 |
+
| No log | 43.0 | 387 | 0.8738 | {'0': {'precision': 0.9477611940298507, 'recall': 0.957286432160804, 'f1-score': 0.9525, 'support': 1592.0}, '1': {'precision': 0.7213114754098361, 'recall': 0.676923076923077, 'f1-score': 0.6984126984126984, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8345363347198433, 'recall': 0.8171047545419405, 'f1-score': 0.8254563492063491, 'support': 1852.0}, 'weighted avg': {'precision': 0.9159701968153778, 'recall': 0.91792656587473, 'f1-score': 0.91682899653742, 'support': 1852.0}} |
|
| 98 |
+
| No log | 44.0 | 396 | 0.8730 | {'0': {'precision': 0.9475327920049968, 'recall': 0.9528894472361809, 'f1-score': 0.9502035703100532, 'support': 1592.0}, '1': {'precision': 0.701195219123506, 'recall': 0.676923076923077, 'f1-score': 0.6888454011741683, 'support': 260.0}, 'accuracy': 0.9141468682505399, 'macro avg': {'precision': 0.8243640055642514, 'recall': 0.8149062620796289, 'f1-score': 0.8195244857421107, 'support': 1852.0}, 'weighted avg': {'precision': 0.9129497634147227, 'recall': 0.9141468682505399, 'f1-score': 0.9135118187035035, 'support': 1852.0}} |
|
| 99 |
+
| No log | 45.0 | 405 | 0.9155 | {'0': {'precision': 0.9448574969021065, 'recall': 0.9579145728643216, 'f1-score': 0.9513412351840299, 'support': 1592.0}, '1': {'precision': 0.7184873949579832, 'recall': 0.6576923076923077, 'f1-score': 0.6867469879518072, 'support': 260.0}, 'accuracy': 0.9157667386609071, 'macro avg': {'precision': 0.8316724459300449, 'recall': 0.8078034402783146, 'f1-score': 0.8190441115679186, 'support': 1852.0}, 'weighted avg': {'precision': 0.9130776769747457, 'recall': 0.9157667386609071, 'f1-score': 0.9141951745574759, 'support': 1852.0}} |
|
| 100 |
+
| No log | 46.0 | 414 | 0.9029 | {'0': {'precision': 0.9465506525792418, 'recall': 0.9566582914572864, 'f1-score': 0.9515776319900031, 'support': 1592.0}, '1': {'precision': 0.7160493827160493, 'recall': 0.6692307692307692, 'f1-score': 0.6918489065606361, 'support': 260.0}, 'accuracy': 0.9163066954643628, 'macro avg': {'precision': 0.8313000176476455, 'recall': 0.8129445303440278, 'f1-score': 0.8217132692753196, 'support': 1852.0}, 'weighted avg': {'precision': 0.91419086307361, 'recall': 0.9163066954643628, 'f1-score': 0.9151146359794009, 'support': 1852.0}} |
|
| 101 |
+
| No log | 47.0 | 423 | 0.9070 | {'0': {'precision': 0.9470734744707348, 'recall': 0.9554020100502513, 'f1-score': 0.9512195121951219, 'support': 1592.0}, '1': {'precision': 0.7113821138211383, 'recall': 0.6730769230769231, 'f1-score': 0.691699604743083, 'support': 260.0}, 'accuracy': 0.9157667386609071, 'macro avg': {'precision': 0.8292277941459365, 'recall': 0.8142394665635873, 'f1-score': 0.8214595584691025, 'support': 1852.0}, 'weighted avg': {'precision': 0.9139850545091284, 'recall': 0.9157667386609071, 'f1-score': 0.9147858318832806, 'support': 1852.0}} |
|
| 102 |
+
| No log | 48.0 | 432 | 0.8932 | {'0': {'precision': 0.9488778054862843, 'recall': 0.9560301507537688, 'f1-score': 0.9524405506883604, 'support': 1592.0}, '1': {'precision': 0.717741935483871, 'recall': 0.6846153846153846, 'f1-score': 0.7007874015748031, 'support': 260.0}, 'accuracy': 0.91792656587473, 'macro avg': {'precision': 0.8333098704850777, 'recall': 0.8203227676845768, 'f1-score': 0.8266139761315818, 'support': 1852.0}, 'weighted avg': {'precision': 0.9164289252483644, 'recall': 0.91792656587473, 'f1-score': 0.9171112748948804, 'support': 1852.0}} |
|
| 103 |
+
| No log | 49.0 | 441 | 0.9557 | {'0': {'precision': 0.9444101297096974, 'recall': 0.960427135678392, 'f1-score': 0.9523512924322641, 'support': 1592.0}, '1': {'precision': 0.7296137339055794, 'recall': 0.6538461538461539, 'f1-score': 0.6896551724137931, 'support': 260.0}, 'accuracy': 0.9173866090712743, 'macro avg': {'precision': 0.8370119318076383, 'recall': 0.807136644762273, 'f1-score': 0.8210032324230286, 'support': 1852.0}, 'weighted avg': {'precision': 0.9142551281389248, 'recall': 0.9173866090712743, 'f1-score': 0.9154717075484615, 'support': 1852.0}} |
|
| 104 |
+
| No log | 50.0 | 450 | 0.9245 | {'0': {'precision': 0.9460297766749379, 'recall': 0.9579145728643216, 'f1-score': 0.9519350811485643, 'support': 1592.0}, '1': {'precision': 0.7208333333333333, 'recall': 0.6653846153846154, 'f1-score': 0.692, 'support': 260.0}, 'accuracy': 0.9168466522678186, 'macro avg': {'precision': 0.8334315550041356, 'recall': 0.8116495941244685, 'f1-score': 0.8219675405742821, 'support': 1852.0}, 'weighted avg': {'precision': 0.914414725233892, 'recall': 0.9168466522678186, 'f1-score': 0.9154431151125887, 'support': 1852.0}} |
|
| 105 |
|
| 106 |
|
| 107 |
### Framework versions
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1583351632
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4fdaab7c134130e066b29c203ea057ba75bdf3dde2dd540adff10a21917648e5
|
| 3 |
size 1583351632
|