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finetune_labelstudio_self_supervised.out
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finetune_labelstudio_self_supervised.out
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nohup: ignoring input
(2749, 10)
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.043 acc:0.000 f1:0.003 precision:0.004 recall:0.002
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.041 acc:0.115 f1:0.168 precision:0.277 recall:0.165
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.040 acc:0.102 f1:0.226 precision:0.239 recall:0.267
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1492: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(
loss:0.040 acc:0.034 f1:0.256 precision:0.232 recall:0.361
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.039 acc:0.034 f1:0.263 precision:0.230 recall:0.391
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.039 acc:0.042 f1:0.298 precision:0.253 recall:0.450
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.026 f1:0.284 precision:0.222 recall:0.480
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.016 f1:0.297 precision:0.236 recall:0.518
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.034 f1:0.298 precision:0.232 recall:0.505
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.034 f1:0.294 precision:0.221 recall:0.512
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.029 f1:0.306 precision:0.235 recall:0.539
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.031 f1:0.313 precision:0.240 recall:0.530
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.047 f1:0.314 precision:0.241 recall:0.532
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.034 f1:0.311 precision:0.232 recall:0.556
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.023 f1:0.322 precision:0.247 recall:0.552
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.036 f1:0.312 precision:0.237 recall:0.521
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.013 f1:0.319 precision:0.243 recall:0.582
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.021 f1:0.315 precision:0.252 recall:0.525
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.026 f1:0.332 precision:0.253 recall:0.588
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.031 f1:0.331 precision:0.253 recall:0.562
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.016 f1:0.329 precision:0.257 recall:0.558
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.016 f1:0.326 precision:0.259 recall:0.567
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.031 f1:0.344 precision:0.268 recall:0.541
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.023 f1:0.341 precision:0.262 recall:0.576
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.010 f1:0.346 precision:0.270 recall:0.581
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.038 acc:0.021 f1:0.324 precision:0.252 recall:0.545
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1492: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(
loss:0.037 acc:0.029 f1:0.342 precision:0.264 recall:0.577
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.013 f1:0.335 precision:0.257 recall:0.565
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
loss:0.037 acc:0.016 f1:0.342 precision:0.261 recall:0.607
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1492: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(
loss:0.038 acc:0.010 f1:0.330 precision:0.248 recall:0.576
/opt/miniconda3/envs/sort_env/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1245: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
Test
loss:0.037 acc:0.029 f1:0.320 precision:0.246 recall:0.518