diff --git "a/experiments/2022-12-21-a12ddf66d95706b1f5f35892f7f60ad628d199c701a09dddd2ad64e8a86a0bae/output.log" "b/experiments/2022-12-21-a12ddf66d95706b1f5f35892f7f60ad628d199c701a09dddd2ad64e8a86a0bae/output.log"
new file mode 100644--- /dev/null
+++ "b/experiments/2022-12-21-a12ddf66d95706b1f5f35892f7f60ad628d199c701a09dddd2ad64e8a86a0bae/output.log"
@@ -0,0 +1,5229 @@
+nohup: ignoring input
+[2022-12-20 17:18:11,002] [WARNING] [runner.py:179:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
+[2022-12-20 17:18:11,035] [INFO] [runner.py:508:main] cmd = /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMCwgMSwgMiwgM119 --master_addr=127.0.0.1 --master_port=29500 tune_gpt.py --deepspeed deepspeed.json
+[2022-12-20 17:18:13,299] [INFO] [launch.py:142:main] WORLD INFO DICT: {'localhost': [0, 1, 2, 3]}
+[2022-12-20 17:18:13,299] [INFO] [launch.py:148:main] nnodes=1, num_local_procs=4, node_rank=0
+[2022-12-20 17:18:13,299] [INFO] [launch.py:161:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1, 2, 3]})
+[2022-12-20 17:18:13,299] [INFO] [launch.py:162:main] dist_world_size=4
+[2022-12-20 17:18:13,299] [INFO] [launch.py:164:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3
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+
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Dataset apps downloaded and prepared to /home/user/.cache/huggingface/datasets/codeparrot___apps/all/0.0.0/04ac807715d07d6e5cc580f59cdc8213cd7dc4529d0bb819cca72c9f8e8c1aa5. Subsequent calls will reuse this data.
+Found cached dataset apps (/home/user/.cache/huggingface/datasets/codeparrot___apps/all/0.0.0/04ac807715d07d6e5cc580f59cdc8213cd7dc4529d0bb819cca72c9f8e8c1aa5)
+Found cached dataset apps (/home/user/.cache/huggingface/datasets/codeparrot___apps/all/0.0.0/04ac807715d07d6e5cc580f59cdc8213cd7dc4529d0bb819cca72c9f8e8c1aa5)
+Found cached dataset apps (/home/user/.cache/huggingface/datasets/codeparrot___apps/all/0.0.0/04ac807715d07d6e5cc580f59cdc8213cd7dc4529d0bb819cca72c9f8e8c1aa5)
+Max length: 2048
+PyTorch: setting up devices
+Max length: 2048
+PyTorch: setting up devices
+[2022-12-20 17:19:24,412] [INFO] [comm.py:654:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+Max length: 2048
+PyTorch: setting up devices
+Max length: 2048
+PyTorch: setting up devices
+The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+GPU memory occupied: 5758 MB.
+GPU memory occupied: 5758 MB.
+GPU memory occupied: 5758 MB.
+GPU memory occupied: 5758 MB.
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Creating extension directory /home/user/.cache/torch_extensions/py38_cu116/cpu_adam...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Detected CUDA files, patching ldflags
+Emitting ninja build file /home/user/.cache/torch_extensions/py38_cu116/cpu_adam/build.ninja...
+Building extension module cpu_adam...
+Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
+[1/3] /usr/local/cuda/bin/nvcc  -DTORCH_EXTENSION_NAME=cpu_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/user/.local/lib/python3.8/site-packages/deepspeed/ops/csrc/includes -I/usr/local/cuda/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/TH -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /usr/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -std=c++14 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_HALF2_OPERATORS__ -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_86,code=compute_86 -c /home/user/.local/lib/python3.8/site-packages/deepspeed/ops/csrc/common/custom_cuda_kernel.cu -o custom_cuda_kernel.cuda.o 
+[2/3] c++ -MMD -MF cpu_adam.o.d -DTORCH_EXTENSION_NAME=cpu_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/user/.local/lib/python3.8/site-packages/deepspeed/ops/csrc/includes -I/usr/local/cuda/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/TH -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /usr/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -O3 -std=c++14 -g -Wno-reorder -L/usr/local/cuda/lib64 -lcudart -lcublas -g -march=native -fopenmp -D__AVX256__ -c /home/user/.local/lib/python3.8/site-packages/deepspeed/ops/csrc/adam/cpu_adam.cpp -o cpu_adam.o 
+[3/3] c++ cpu_adam.o custom_cuda_kernel.cuda.o -shared -lcurand -L/home/user/.local/lib/python3.8/site-packages/torch/lib -lc10 -lc10_cuda -ltorch_cpu -ltorch_cuda_cu -ltorch_cuda_cpp -ltorch -ltorch_python -L/usr/local/cuda/lib64 -lcudart -o cpu_adam.so
+Loading extension module cpu_adam...
+Time to load cpu_adam op: 39.87346434593201 seconds
+Loading extension module cpu_adam...
+Time to load cpu_adam op: 39.953386545181274 seconds
+Loading extension module cpu_adam...
+Time to load cpu_adam op: 39.9042444229126 seconds
+Loading extension module cpu_adam...
+Time to load cpu_adam op: 39.96823048591614 seconds
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Creating extension directory /home/user/.cache/torch_extensions/py38_cu116/utils...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+Emitting ninja build file /home/user/.cache/torch_extensions/py38_cu116/utils/build.ninja...
+Building extension module utils...
+Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
+[1/2] c++ -MMD -MF flatten_unflatten.o.d -DTORCH_EXTENSION_NAME=utils -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/user/.local/lib/python3.8/site-packages/torch/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/TH -isystem /home/user/.local/lib/python3.8/site-packages/torch/include/THC -isystem /usr/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -c /home/user/.local/lib/python3.8/site-packages/deepspeed/ops/csrc/utils/flatten_unflatten.cpp -o flatten_unflatten.o 
+[2/2] c++ flatten_unflatten.o -shared -L/home/user/.local/lib/python3.8/site-packages/torch/lib -lc10 -ltorch_cpu -ltorch -ltorch_python -o utils.so
+Loading extension module utils...
+Time to load utils op: 23.038707971572876 seconds
+Loading extension module utils...
+Time to load utils op: 22.962859392166138 seconds
+Loading extension module utils...
+Time to load utils op: 22.961502075195312 seconds
+Loading extension module utils...
+Time to load utils op: 23.0585675239563 seconds
+Rank: 2 partition count [4] and sizes[(31299648, False)] 
+Rank: 3 partition count [4] and sizes[(31299648, False)] 
+Rank: 1 partition count [4] and sizes[(31299648, False)] 
+Rank: 0 partition count [4] and sizes[(31299648, False)] 
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+No modifications detected for re-loaded extension module utils, skipping build step...
+Loading extension module utils...
+Time to load utils op: 0.0010988712310791016 seconds
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+No modifications detected for re-loaded extension module utils, skipping build step...
+Loading extension module utils...
+Time to load utils op: 0.0008800029754638672 seconds
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+No modifications detected for re-loaded extension module utils, skipping build step...
+Loading extension module utils...
+Time to load utils op: 0.0007402896881103516 seconds
+Using /home/user/.cache/torch_extensions/py38_cu116 as PyTorch extensions root...
+No modifications detected for re-loaded extension module utils, skipping build step...
+Loading extension module utils...
+Time to load utils op: 0.0005016326904296875 seconds
+
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+  warnings.warn(
+/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py:1432: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+  warnings.warn(
+/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py:1432: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+  warnings.warn(
+/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py:1432: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+  warnings.warn(
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{'loss': 0.3722, 'learning_rate': 4.589012198616609e-05, 'epoch': 0.06}
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{'loss': 0.3887, 'learning_rate': 4.602310947056923e-05, 'epoch': 0.06}
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{'loss': 0.4047, 'learning_rate': 4.615393446077182e-05, 'epoch': 0.06}
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{'loss': 0.343, 'learning_rate': 4.6282666161090166e-05, 'epoch': 0.06}
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{'loss': 0.351, 'learning_rate': 4.640937050606839e-05, 'epoch': 0.07}
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{'loss': 0.3758, 'learning_rate': 4.653411036327597e-05, 'epoch': 0.07}
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{'loss': 0.3506, 'learning_rate': 4.665694572062267e-05, 'epoch': 0.07}
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{'loss': 0.3582, 'learning_rate': 4.677793385958802e-05, 'epoch': 0.07}
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{'loss': 0.3527, 'learning_rate': 4.689712951561742e-05, 'epoch': 0.07}
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{'loss': 0.4034, 'learning_rate': 4.701458502680934e-05, 'epoch': 0.07}
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{'loss': 0.4317, 'learning_rate': 4.713035047190436e-05, 'epoch': 0.07}
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{'loss': 0.3733, 'learning_rate': 4.7244473798486756e-05, 'epoch': 0.07}
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{'loss': 0.3894, 'learning_rate': 4.735700094222001e-05, 'epoch': 0.07}
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{'loss': 0.3961, 'learning_rate': 4.746797593785841e-05, 'epoch': 0.07}
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{'loss': 0.4013, 'learning_rate': 4.7577441022706095e-05, 'epoch': 0.08}
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{'loss': 0.3634, 'learning_rate': 4.76854367331319e-05, 'epoch': 0.08}
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{'loss': 0.358, 'learning_rate': 4.7792001994691866e-05, 'epoch': 0.08}
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{'loss': 0.3685, 'learning_rate': 4.7897174206360945e-05, 'epoch': 0.08}
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{'loss': 0.3448, 'learning_rate': 4.800098931932989e-05, 'epoch': 0.08}
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{'loss': 0.3617, 'learning_rate': 4.810348191078279e-05, 'epoch': 0.08}
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{'loss': 0.3189, 'learning_rate': 4.82046852530342e-05, 'epoch': 0.08}
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{'loss': 0.3415, 'learning_rate': 4.830463137837162e-05, 'epoch': 0.08}
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{'loss': 0.3917, 'learning_rate': 4.8403351139919656e-05, 'epoch': 0.08}
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{'loss': 0.3584, 'learning_rate': 4.850087426881512e-05, 'epoch': 0.08}
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{'loss': 0.3367, 'learning_rate': 4.859722942795827e-05, 'epoch': 0.09}
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{'loss': 0.3694, 'learning_rate': 4.8692444262583224e-05, 'epoch': 0.09}
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{'loss': 0.3636, 'learning_rate': 4.8786545447870833e-05, 'epoch': 0.09}
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{'loss': 0.3147, 'learning_rate': 4.8879558733809264e-05, 'epoch': 0.09}
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{'loss': 0.3436, 'learning_rate': 4.897150898749078e-05, 'epoch': 0.09}
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{'loss': 0.3808, 'learning_rate': 4.9062420233018894e-05, 'epoch': 0.09}
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{'loss': 0.326, 'learning_rate': 4.915231568918581e-05, 'epoch': 0.09}
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{'loss': 0.3527, 'learning_rate': 4.924121780506815e-05, 'epoch': 0.09}
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{'loss': 0.3319, 'learning_rate': 4.932914829367744e-05, 'epoch': 0.09}
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{'loss': 0.3662, 'learning_rate': 4.941612816379154e-05, 'epoch': 0.1}
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{'loss': 0.3433, 'learning_rate': 4.950217775008374e-05, 'epoch': 0.1}
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{'loss': 0.3392, 'learning_rate': 4.958731674165767e-05, 'epoch': 0.1}
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{'loss': 0.3569, 'learning_rate': 4.967156420908811e-05, 'epoch': 0.1}
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{'loss': 0.3795, 'learning_rate': 4.975493863006067e-05, 'epoch': 0.1}
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{'loss': 0.3499, 'learning_rate': 4.9837457913696535e-05, 'epoch': 0.1}
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{'loss': 0.3757, 'learning_rate': 4.99191394236424e-05, 'epoch': 0.1}
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{'loss': 0.3545, 'learning_rate': 5e-05, 'epoch': 0.1}
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{'loss': 0.3111, 'learning_rate': 5e-05, 'epoch': 0.1}
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{'loss': 0.3516, 'learning_rate': 5e-05, 'epoch': 0.1}
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{'loss': 0.3211, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.342, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3216, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3076, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3308, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3662, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3298, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3414, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3214, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3061, 'learning_rate': 5e-05, 'epoch': 0.11}
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{'loss': 0.3408, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.2838, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3027, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.2984, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3014, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3216, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3158, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3583, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3694, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3198, 'learning_rate': 5e-05, 'epoch': 0.12}
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{'loss': 0.3439, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3304, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3174, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3669, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3423, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3082, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3171, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3514, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.325, 'learning_rate': 5e-05, 'epoch': 0.13}
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{'loss': 0.3285, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3328, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3433, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3275, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3258, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3089, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.2906, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3108, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.3375, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.2871, 'learning_rate': 5e-05, 'epoch': 0.14}
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{'loss': 0.33, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3167, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3093, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.2909, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.322, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3315, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.312, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3214, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3292, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3413, 'learning_rate': 5e-05, 'epoch': 0.15}
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{'loss': 0.3192, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.394, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3246, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3426, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3202, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3052, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.2478, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3349, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3273, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3127, 'learning_rate': 5e-05, 'epoch': 0.16}
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{'loss': 0.3093, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.2677, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.3068, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.345, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.2935, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.3186, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.2834, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.3061, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.2804, 'learning_rate': 5e-05, 'epoch': 0.17}
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{'loss': 0.2772, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2997, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2813, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.3031, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.3064, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2915, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.3091, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.3146, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2902, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2727, 'learning_rate': 5e-05, 'epoch': 0.18}
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{'loss': 0.2739, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.3088, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.3228, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.3177, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.2883, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.299, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.2757, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.2734, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.3084, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.2849, 'learning_rate': 5e-05, 'epoch': 0.19}
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{'loss': 0.2798, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.3177, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.2927, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.3056, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.2921, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.303, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.3001, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.2754, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.2996, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.2837, 'learning_rate': 5e-05, 'epoch': 0.2}
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{'loss': 0.28, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2569, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.3024, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.3372, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2974, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2759, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2839, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2764, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2955, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2835, 'learning_rate': 5e-05, 'epoch': 0.21}
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{'loss': 0.2527, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2705, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2824, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2612, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2579, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.281, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2812, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.3327, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2649, 'learning_rate': 5e-05, 'epoch': 0.22}
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{'loss': 0.2614, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2708, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2765, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.3124, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.29, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2725, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2483, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.329, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.259, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2863, 'learning_rate': 5e-05, 'epoch': 0.23}
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{'loss': 0.2753, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.24, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2579, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2808, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.3037, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2912, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2184, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.3175, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.202, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2754, 'learning_rate': 5e-05, 'epoch': 0.24}
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{'loss': 0.2688, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2579, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2951, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2739, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2754, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2557, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2894, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2559, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.243, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.2456, 'learning_rate': 5e-05, 'epoch': 0.25}
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{'loss': 0.3231, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2295, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.3158, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2281, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2526, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2462, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2464, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2602, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.3167, 'learning_rate': 5e-05, 'epoch': 0.26}
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{'loss': 0.2821, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.269, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2565, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2554, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.249, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2422, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2476, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2738, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2701, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2614, 'learning_rate': 5e-05, 'epoch': 0.27}
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{'loss': 0.2793, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2378, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2688, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2408, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2226, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2443, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2474, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2272, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2488, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2791, 'learning_rate': 5e-05, 'epoch': 0.28}
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{'loss': 0.2543, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2502, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2556, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2665, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2558, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2745, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2886, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2268, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2794, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.2012, 'learning_rate': 5e-05, 'epoch': 0.29}
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{'loss': 0.257, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.275, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2422, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2112, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2483, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2346, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2374, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2144, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2364, 'learning_rate': 5e-05, 'epoch': 0.3}
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{'loss': 0.2561, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2271, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2078, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2501, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2819, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2676, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2082, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2684, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2237, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2576, 'learning_rate': 5e-05, 'epoch': 0.31}
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{'loss': 0.2427, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2747, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2769, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2379, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2243, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2347, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2362, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2249, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2561, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2148, 'learning_rate': 5e-05, 'epoch': 0.32}
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{'loss': 0.2157, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.264, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2187, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2457, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2215, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2351, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2594, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2423, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2544, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2286, 'learning_rate': 5e-05, 'epoch': 0.33}
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{'loss': 0.2312, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2458, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2286, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2359, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2255, 'learning_rate': 5e-05, 'epoch': 0.34}
+
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{'loss': 0.2265, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.264, 'learning_rate': 5e-05, 'epoch': 0.34}
+
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{'loss': 0.2411, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2415, 'learning_rate': 5e-05, 'epoch': 0.34}
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{'loss': 0.2374, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2229, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2325, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2499, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2193, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2371, 'learning_rate': 5e-05, 'epoch': 0.35}
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{'loss': 0.2188, 'learning_rate': 5e-05, 'epoch': 0.35}
+
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{'loss': 0.25, 'learning_rate': 5e-05, 'epoch': 0.35}
+
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{'loss': 0.2415, 'learning_rate': 5e-05, 'epoch': 0.35}
+
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{'loss': 0.2637, 'learning_rate': 5e-05, 'epoch': 0.35}
+
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{'loss': 0.254, 'learning_rate': 5e-05, 'epoch': 0.36}
+
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{'loss': 0.2594, 'learning_rate': 5e-05, 'epoch': 0.36}
+
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{'loss': 0.2366, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2384, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2516, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2556, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2742, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2246, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2086, 'learning_rate': 5e-05, 'epoch': 0.36}
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{'loss': 0.2172, 'learning_rate': 5e-05, 'epoch': 0.36}
+
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{'loss': 0.206, 'learning_rate': 5e-05, 'epoch': 0.37}
+
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{'loss': 0.2153, 'learning_rate': 5e-05, 'epoch': 0.37}
+
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{'loss': 0.2361, 'learning_rate': 5e-05, 'epoch': 0.37}
+
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{'loss': 0.2589, 'learning_rate': 5e-05, 'epoch': 0.37}
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{'loss': 0.2523, 'learning_rate': 5e-05, 'epoch': 0.37}
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{'loss': 0.2082, 'learning_rate': 5e-05, 'epoch': 0.37}
+
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{'loss': 0.2021, 'learning_rate': 5e-05, 'epoch': 0.37}
+
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{'loss': 0.2466, 'learning_rate': 5e-05, 'epoch': 0.37}
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{'loss': 0.1922, 'learning_rate': 5e-05, 'epoch': 0.37}
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  7%|▋         | 1828/24420 [45:23<9:14:08,  1.47s/it]
  7%|▋         | 1829/24420 [45:24<9:13:32,  1.47s/it]
  7%|▋         | 1830/24420 [45:26<9:13:48,  1.47s/it]
                                                      
{'loss': 0.2358, 'learning_rate': 5e-05, 'epoch': 0.37}
+
  7%|▋         | 1830/24420 [45:26<9:13:48,  1.47s/it]
  7%|▋         | 1831/24420 [45:27<9:14:06,  1.47s/it]
  8%|▊         | 1832/24420 [45:29<9:14:03,  1.47s/it]
  8%|▊         | 1833/24420 [45:30<9:13:20,  1.47s/it]
  8%|▊         | 1834/24420 [45:32<9:14:07,  1.47s/it]
  8%|▊         | 1835/24420 [45:33<9:14:43,  1.47s/it]
                                                      
{'loss': 0.2286, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1835/24420 [45:33<9:14:43,  1.47s/it]
  8%|▊         | 1836/24420 [45:35<9:15:16,  1.48s/it]
  8%|▊         | 1837/24420 [45:36<9:15:45,  1.48s/it]
  8%|▊         | 1838/24420 [45:38<9:15:10,  1.48s/it]
  8%|▊         | 1839/24420 [45:39<9:14:44,  1.47s/it]
  8%|▊         | 1840/24420 [45:41<9:13:51,  1.47s/it]
                                                      
{'loss': 0.224, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1840/24420 [45:41<9:13:51,  1.47s/it]
  8%|▊         | 1841/24420 [45:42<9:13:32,  1.47s/it]
  8%|▊         | 1842/24420 [45:44<9:13:36,  1.47s/it]
  8%|▊         | 1843/24420 [45:45<9:14:09,  1.47s/it]
  8%|▊         | 1844/24420 [45:47<9:14:55,  1.47s/it]
  8%|▊         | 1845/24420 [45:48<9:13:59,  1.47s/it]
                                                      
{'loss': 0.224, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1845/24420 [45:48<9:13:59,  1.47s/it]
  8%|▊         | 1846/24420 [45:50<9:15:02,  1.48s/it]
  8%|▊         | 1847/24420 [45:51<9:14:41,  1.47s/it]
  8%|▊         | 1848/24420 [45:52<9:13:59,  1.47s/it]
  8%|▊         | 1849/24420 [45:54<9:14:22,  1.47s/it]
  8%|▊         | 1850/24420 [45:55<9:14:06,  1.47s/it]
                                                      
{'loss': 0.2461, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1850/24420 [45:55<9:14:06,  1.47s/it]
  8%|▊         | 1851/24420 [45:57<9:14:41,  1.47s/it]
  8%|▊         | 1852/24420 [45:58<9:14:04,  1.47s/it]
  8%|▊         | 1853/24420 [46:00<9:13:53,  1.47s/it]
  8%|▊         | 1854/24420 [46:01<9:14:17,  1.47s/it]
  8%|▊         | 1855/24420 [46:03<9:13:13,  1.47s/it]
                                                      
{'loss': 0.221, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1855/24420 [46:03<9:13:13,  1.47s/it]
  8%|▊         | 1856/24420 [46:04<9:13:53,  1.47s/it]
  8%|▊         | 1857/24420 [46:06<9:13:53,  1.47s/it]
  8%|▊         | 1858/24420 [46:07<9:14:17,  1.47s/it]
  8%|▊         | 1859/24420 [46:09<9:13:55,  1.47s/it]
  8%|▊         | 1860/24420 [46:10<9:13:47,  1.47s/it]
                                                      
{'loss': 0.262, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1860/24420 [46:10<9:13:47,  1.47s/it]
  8%|▊         | 1861/24420 [46:12<9:14:30,  1.47s/it]
  8%|▊         | 1862/24420 [46:13<9:14:14,  1.47s/it]
  8%|▊         | 1863/24420 [46:15<9:13:30,  1.47s/it]
  8%|▊         | 1864/24420 [46:16<9:12:52,  1.47s/it]
  8%|▊         | 1865/24420 [46:17<9:12:19,  1.47s/it]
                                                      
{'loss': 0.2015, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1865/24420 [46:17<9:12:19,  1.47s/it]
  8%|▊         | 1866/24420 [46:19<9:12:40,  1.47s/it]
  8%|▊         | 1867/24420 [46:20<9:12:48,  1.47s/it]
  8%|▊         | 1868/24420 [46:22<9:13:18,  1.47s/it]
  8%|▊         | 1869/24420 [46:23<9:13:57,  1.47s/it]
  8%|▊         | 1870/24420 [46:25<9:12:56,  1.47s/it]
                                                      
{'loss': 0.2159, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1870/24420 [46:25<9:12:56,  1.47s/it]
  8%|▊         | 1871/24420 [46:26<9:13:55,  1.47s/it]
  8%|���         | 1872/24420 [46:28<9:13:44,  1.47s/it]
  8%|▊         | 1873/24420 [46:29<9:14:13,  1.47s/it]
  8%|▊         | 1874/24420 [46:31<9:13:48,  1.47s/it]
  8%|▊         | 1875/24420 [46:32<9:14:19,  1.48s/it]
                                                      
{'loss': 0.2412, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1875/24420 [46:32<9:14:19,  1.48s/it]
  8%|▊         | 1876/24420 [46:34<9:14:44,  1.48s/it]
  8%|▊         | 1877/24420 [46:35<9:14:43,  1.48s/it]
  8%|▊         | 1878/24420 [46:37<9:13:21,  1.47s/it]
  8%|▊         | 1879/24420 [46:38<9:13:04,  1.47s/it]
  8%|▊         | 1880/24420 [46:40<9:12:57,  1.47s/it]
                                                      
{'loss': 0.2015, 'learning_rate': 5e-05, 'epoch': 0.38}
+
  8%|▊         | 1880/24420 [46:40<9:12:57,  1.47s/it]
  8%|▊         | 1881/24420 [46:41<9:12:51,  1.47s/it]
  8%|▊         | 1882/24420 [46:43<9:12:28,  1.47s/it]
  8%|▊         | 1883/24420 [46:44<9:13:16,  1.47s/it]
  8%|▊         | 1884/24420 [46:45<9:13:48,  1.47s/it]
  8%|▊         | 1885/24420 [46:47<9:13:11,  1.47s/it]
                                                      
{'loss': 0.2328, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1885/24420 [46:47<9:13:11,  1.47s/it]
  8%|▊         | 1886/24420 [46:48<9:12:56,  1.47s/it]
  8%|▊         | 1887/24420 [46:50<9:13:45,  1.47s/it]
  8%|▊         | 1888/24420 [46:51<9:13:20,  1.47s/it]
  8%|▊         | 1889/24420 [46:53<9:13:10,  1.47s/it]
  8%|▊         | 1890/24420 [46:54<9:13:01,  1.47s/it]
                                                      
{'loss': 0.2384, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1890/24420 [46:54<9:13:01,  1.47s/it]
  8%|▊         | 1891/24420 [46:56<9:13:20,  1.47s/it]
  8%|▊         | 1892/24420 [46:57<9:12:52,  1.47s/it]
  8%|▊         | 1893/24420 [46:59<9:12:56,  1.47s/it]
  8%|▊         | 1894/24420 [47:00<9:13:00,  1.47s/it]
  8%|▊         | 1895/24420 [47:02<9:13:54,  1.48s/it]
                                                      
{'loss': 0.2342, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1895/24420 [47:02<9:13:54,  1.48s/it]
  8%|▊         | 1896/24420 [47:03<9:13:19,  1.47s/it]
  8%|▊         | 1897/24420 [47:05<9:12:20,  1.47s/it]
  8%|▊         | 1898/24420 [47:06<9:12:36,  1.47s/it]
  8%|▊         | 1899/24420 [47:08<9:12:20,  1.47s/it]
  8%|▊         | 1900/24420 [47:09<9:13:00,  1.47s/it]
                                                      
{'loss': 0.2272, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1900/24420 [47:09<9:13:00,  1.47s/it]
  8%|▊         | 1901/24420 [47:11<9:12:52,  1.47s/it]
  8%|▊         | 1902/24420 [47:12<9:12:54,  1.47s/it]
  8%|▊         | 1903/24420 [47:13<9:13:20,  1.47s/it]
  8%|▊         | 1904/24420 [47:15<9:12:43,  1.47s/it]
  8%|▊         | 1905/24420 [47:16<9:13:14,  1.47s/it]
                                                      
{'loss': 0.241, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1905/24420 [47:16<9:13:14,  1.47s/it]
  8%|▊         | 1906/24420 [47:18<9:13:22,  1.47s/it]
  8%|▊         | 1907/24420 [47:19<9:13:43,  1.48s/it]
  8%|▊         | 1908/24420 [47:21<9:13:30,  1.48s/it]
  8%|▊         | 1909/24420 [47:22<9:13:06,  1.47s/it]
  8%|▊         | 1910/24420 [47:24<9:12:07,  1.47s/it]
                                                      
{'loss': 0.2538, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1910/24420 [47:24<9:12:07,  1.47s/it]
  8%|▊         | 1911/24420 [47:25<9:12:09,  1.47s/it]
  8%|▊         | 1912/24420 [47:27<9:11:24,  1.47s/it]
  8%|▊         | 1913/24420 [47:28<9:11:07,  1.47s/it]
  8%|▊         | 1914/24420 [47:30<9:12:50,  1.47s/it]
  8%|▊         | 1915/24420 [47:31<9:14:33,  1.48s/it]
                                                      
{'loss': 0.2412, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1915/24420 [47:31<9:14:33,  1.48s/it]
  8%|▊         | 1916/24420 [47:33<9:14:34,  1.48s/it]
  8%|▊         | 1917/24420 [47:34<9:14:20,  1.48s/it]
  8%|▊         | 1918/24420 [47:36<9:13:42,  1.48s/it]
  8%|▊         | 1919/24420 [47:37<9:13:27,  1.48s/it]
  8%|▊         | 1920/24420 [47:39<9:14:05,  1.48s/it]
                                                      
{'loss': 0.2372, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1920/24420 [47:39<9:14:05,  1.48s/it]
  8%|▊         | 1921/24420 [47:40<9:13:39,  1.48s/it]
  8%|▊         | 1922/24420 [47:41<9:12:57,  1.47s/it]
  8%|▊         | 1923/24420 [47:43<9:12:46,  1.47s/it]
  8%|▊         | 1924/24420 [47:44<9:12:32,  1.47s/it]
  8%|▊         | 1925/24420 [47:46<9:11:47,  1.47s/it]
                                                      
{'loss': 0.2155, 'learning_rate': 5e-05, 'epoch': 0.39}
+
  8%|▊         | 1925/24420 [47:46<9:11:47,  1.47s/it]
  8%|▊         | 1926/24420 [47:47<9:11:43,  1.47s/it]
  8%|▊         | 1927/24420 [47:49<9:11:14,  1.47s/it]
  8%|▊         | 1928/24420 [47:50<9:11:04,  1.47s/it]
  8%|▊         | 1929/24420 [47:52<9:11:30,  1.47s/it]
  8%|▊         | 1930/24420 [47:53<9:12:07,  1.47s/it]
                                                      
{'loss': 0.2107, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1930/24420 [47:53<9:12:07,  1.47s/it]
  8%|▊         | 1931/24420 [47:55<9:11:57,  1.47s/it]
  8%|▊         | 1932/24420 [47:56<9:11:49,  1.47s/it]
  8%|▊         | 1933/24420 [47:58<9:11:56,  1.47s/it]
  8%|▊         | 1934/24420 [47:59<9:12:35,  1.47s/it]
  8%|▊         | 1935/24420 [48:01<9:12:12,  1.47s/it]
                                                      
{'loss': 0.218, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1935/24420 [48:01<9:12:12,  1.47s/it]
  8%|▊         | 1936/24420 [48:02<9:11:27,  1.47s/it]
  8%|▊         | 1937/24420 [48:04<9:12:32,  1.47s/it]
  8%|▊         | 1938/24420 [48:05<9:12:43,  1.48s/it]
  8%|▊         | 1939/24420 [48:07<9:13:08,  1.48s/it]
  8%|▊         | 1940/24420 [48:08<9:12:16,  1.47s/it]
                                                      
{'loss': 0.2291, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1940/24420 [48:08<9:12:16,  1.47s/it]
  8%|▊         | 1941/24420 [48:09<9:12:33,  1.47s/it]
  8%|▊         | 1942/24420 [48:11<9:12:24,  1.47s/it]
  8%|▊         | 1943/24420 [48:12<9:12:22,  1.47s/it]
  8%|▊         | 1944/24420 [48:14<9:11:47,  1.47s/it]
  8%|▊         | 1945/24420 [48:15<9:10:59,  1.47s/it]
                                                      
{'loss': 0.2221, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1945/24420 [48:15<9:10:59,  1.47s/it]
  8%|▊         | 1946/24420 [48:17<9:10:16,  1.47s/it]
  8%|▊         | 1947/24420 [48:18<9:09:37,  1.47s/it]
  8%|▊         | 1948/24420 [48:20<9:09:23,  1.47s/it]
  8%|▊         | 1949/24420 [48:21<9:10:27,  1.47s/it]
  8%|▊         | 1950/24420 [48:23<9:10:31,  1.47s/it]
                                                      
{'loss': 0.2072, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1950/24420 [48:23<9:10:31,  1.47s/it]
  8%|▊         | 1951/24420 [48:24<9:10:33,  1.47s/it]
  8%|▊         | 1952/24420 [48:26<9:10:03,  1.47s/it]
  8%|▊         | 1953/24420 [48:27<9:10:40,  1.47s/it]
  8%|▊         | 1954/24420 [48:29<9:10:49,  1.47s/it]
  8%|▊         | 1955/24420 [48:30<9:12:13,  1.47s/it]
                                                      
{'loss': 0.2286, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1955/24420 [48:30<9:12:13,  1.47s/it]
  8%|▊         | 1956/24420 [48:32<9:12:46,  1.48s/it]
  8%|▊         | 1957/24420 [48:33<9:12:31,  1.48s/it]
  8%|▊         | 1958/24420 [48:35<9:11:59,  1.47s/it]
  8%|▊         | 1959/24420 [48:36<9:11:01,  1.47s/it]
  8%|▊         | 1960/24420 [48:37<9:10:31,  1.47s/it]
                                                      
{'loss': 0.2217, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1960/24420 [48:37<9:10:31,  1.47s/it]
  8%|▊         | 1961/24420 [48:39<9:09:54,  1.47s/it]
  8%|▊         | 1962/24420 [48:40<9:10:00,  1.47s/it]
  8%|▊         | 1963/24420 [48:42<9:11:25,  1.47s/it]
  8%|▊         | 1964/24420 [48:43<9:11:06,  1.47s/it]
  8%|▊         | 1965/24420 [48:45<9:11:32,  1.47s/it]
                                                      
{'loss': 0.2102, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1965/24420 [48:45<9:11:32,  1.47s/it]
  8%|▊         | 1966/24420 [48:46<9:12:07,  1.48s/it]
  8%|▊         | 1967/24420 [48:48<9:12:46,  1.48s/it]
  8%|▊         | 1968/24420 [48:49<9:12:11,  1.48s/it]
  8%|▊         | 1969/24420 [48:51<9:13:10,  1.48s/it]
  8%|▊         | 1970/24420 [48:52<9:12:26,  1.48s/it]
                                                      
{'loss': 0.2508, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1970/24420 [48:52<9:12:26,  1.48s/it]
  8%|▊         | 1971/24420 [48:54<9:11:44,  1.47s/it]
  8%|▊         | 1972/24420 [48:55<9:11:21,  1.47s/it]
  8%|▊         | 1973/24420 [48:57<9:10:37,  1.47s/it]
  8%|▊         | 1974/24420 [48:58<9:09:58,  1.47s/it]
  8%|▊         | 1975/24420 [49:00<9:11:06,  1.47s/it]
                                                      
{'loss': 0.2274, 'learning_rate': 5e-05, 'epoch': 0.4}
+
  8%|▊         | 1975/24420 [49:00<9:11:06,  1.47s/it]
  8%|▊         | 1976/24420 [49:01<9:11:19,  1.47s/it]
  8%|▊         | 1977/24420 [49:02<9:10:51,  1.47s/it]
  8%|▊         | 1978/24420 [49:04<9:10:51,  1.47s/it]
  8%|▊         | 1979/24420 [49:05<9:11:14,  1.47s/it]
  8%|▊         | 1980/24420 [49:07<9:11:10,  1.47s/it]
                                                      
{'loss': 0.1963, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 1980/24420 [49:07<9:11:10,  1.47s/it]
  8%|▊         | 1981/24420 [49:08<9:11:14,  1.47s/it]
  8%|▊         | 1982/24420 [49:10<9:10:52,  1.47s/it]
  8%|▊         | 1983/24420 [49:11<9:10:00,  1.47s/it]
  8%|▊         | 1984/24420 [49:13<9:09:34,  1.47s/it]
  8%|▊         | 1985/24420 [49:14<9:09:25,  1.47s/it]
                                                      
{'loss': 0.2006, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 1985/24420 [49:14<9:09:25,  1.47s/it]
  8%|▊         | 1986/24420 [49:16<9:09:32,  1.47s/it]
  8%|▊         | 1987/24420 [49:17<9:09:33,  1.47s/it]
  8%|▊         | 1988/24420 [49:19<9:09:54,  1.47s/it]
  8%|▊         | 1989/24420 [49:20<9:09:34,  1.47s/it]
  8%|▊         | 1990/24420 [49:22<9:10:11,  1.47s/it]
                                                      
{'loss': 0.2203, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 1990/24420 [49:22<9:10:11,  1.47s/it]
  8%|▊         | 1991/24420 [49:23<9:09:31,  1.47s/it]
  8%|▊         | 1992/24420 [49:25<9:09:49,  1.47s/it]
  8%|▊         | 1993/24420 [49:26<9:10:19,  1.47s/it]
  8%|▊         | 1994/24420 [49:28<9:10:30,  1.47s/it]
  8%|▊         | 1995/24420 [49:29<9:10:51,  1.47s/it]
                                                      
{'loss': 0.2323, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 1995/24420 [49:29<9:10:51,  1.47s/it]
  8%|▊         | 1996/24420 [49:30<9:10:53,  1.47s/it]
  8%|▊         | 1997/24420 [49:32<9:10:41,  1.47s/it]
  8%|▊         | 1998/24420 [49:33<9:11:17,  1.48s/it]
  8%|▊         | 1999/24420 [49:35<9:10:36,  1.47s/it]
  8%|▊         | 2000/24420 [49:36<9:09:36,  1.47s/it]
                                                      
{'loss': 0.2549, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2000/24420 [49:36<9:09:36,  1.47s/it]
  8%|▊         | 2001/24420 [49:41<14:50:56,  2.38s/it]
  8%|▊         | 2002/24420 [49:42<13:08:38,  2.11s/it]
  8%|▊         | 2003/24420 [49:44<11:58:28,  1.92s/it]
  8%|▊         | 2004/24420 [49:45<11:07:48,  1.79s/it]
  8%|▊         | 2005/24420 [49:47<10:32:12,  1.69s/it]
                                                       
{'loss': 0.2149, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2005/24420 [49:47<10:32:12,  1.69s/it]
  8%|▊         | 2006/24420 [49:48<10:07:32,  1.63s/it]
  8%|▊         | 2007/24420 [49:50<9:50:27,  1.58s/it] 
  8%|▊         | 2008/24420 [49:51<9:39:24,  1.55s/it]
  8%|▊         | 2009/24420 [49:53<9:30:42,  1.53s/it]
  8%|▊         | 2010/24420 [49:54<9:24:07,  1.51s/it]
                                                      
{'loss': 0.2191, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2010/24420 [49:54<9:24:07,  1.51s/it]
  8%|▊         | 2011/24420 [49:56<9:19:00,  1.50s/it]
  8%|▊         | 2012/24420 [49:57<9:16:20,  1.49s/it]
  8%|▊         | 2013/24420 [49:59<9:15:17,  1.49s/it]
  8%|▊         | 2014/24420 [50:00<9:13:56,  1.48s/it]
  8%|▊         | 2015/24420 [50:01<9:12:30,  1.48s/it]
                                                      
{'loss': 0.23, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2015/24420 [50:01<9:12:30,  1.48s/it]
  8%|▊         | 2016/24420 [50:03<9:12:01,  1.48s/it]
  8%|▊         | 2017/24420 [50:04<9:11:45,  1.48s/it]
  8%|▊         | 2018/24420 [50:06<9:10:41,  1.47s/it]
  8%|▊         | 2019/24420 [50:07<9:10:35,  1.47s/it]
  8%|▊         | 2020/24420 [50:09<9:10:19,  1.47s/it]
                                                      
{'loss': 0.2197, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2020/24420 [50:09<9:10:19,  1.47s/it]
  8%|▊         | 2021/24420 [50:10<9:12:04,  1.48s/it]
  8%|▊         | 2022/24420 [50:12<9:11:49,  1.48s/it]
  8%|▊         | 2023/24420 [50:13<9:10:49,  1.48s/it]
  8%|▊         | 2024/24420 [50:15<9:10:52,  1.48s/it]
  8%|▊         | 2025/24420 [50:16<9:10:11,  1.47s/it]
                                                      
{'loss': 0.2092, 'learning_rate': 5e-05, 'epoch': 0.41}
+
  8%|▊         | 2025/24420 [50:16<9:10:11,  1.47s/it]
  8%|▊         | 2026/24420 [50:18<9:09:56,  1.47s/it]
  8%|▊         | 2027/24420 [50:19<9:09:35,  1.47s/it]
  8%|▊         | 2028/24420 [50:21<9:11:53,  1.48s/it]
  8%|▊         | 2029/24420 [50:22<9:10:25,  1.47s/it]
  8%|▊         | 2030/24420 [50:24<9:10:06,  1.47s/it]
                                                      
{'loss': 0.21, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2030/24420 [50:24<9:10:06,  1.47s/it]
  8%|▊         | 2031/24420 [50:25<9:09:57,  1.47s/it]
  8%|▊         | 2032/24420 [50:27<9:08:49,  1.47s/it]
  8%|▊         | 2033/24420 [50:28<9:09:59,  1.47s/it]
  8%|▊         | 2034/24420 [50:30<9:09:17,  1.47s/it]
  8%|▊         | 2035/24420 [50:31<9:09:10,  1.47s/it]
                                                      
{'loss': 0.2282, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2035/24420 [50:31<9:09:10,  1.47s/it]
  8%|▊         | 2036/24420 [50:32<9:08:40,  1.47s/it]
  8%|▊         | 2037/24420 [50:34<9:09:07,  1.47s/it]
  8%|▊         | 2038/24420 [50:35<9:09:52,  1.47s/it]
  8%|▊         | 2039/24420 [50:37<9:09:39,  1.47s/it]
  8%|▊         | 2040/24420 [50:38<9:08:56,  1.47s/it]
                                                      
{'loss': 0.2276, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2040/24420 [50:38<9:08:56,  1.47s/it]
  8%|▊         | 2041/24420 [50:40<9:10:20,  1.48s/it]
  8%|▊         | 2042/24420 [50:41<9:11:09,  1.48s/it]
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  8%|▊         | 2044/24420 [50:44<9:09:43,  1.47s/it]
  8%|▊         | 2045/24420 [50:46<9:09:49,  1.47s/it]
                                                      
{'loss': 0.2129, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2045/24420 [50:46<9:09:49,  1.47s/it]
  8%|▊         | 2046/24420 [50:47<9:09:39,  1.47s/it]
  8%|▊         | 2047/24420 [50:49<9:08:47,  1.47s/it]
  8%|▊         | 2048/24420 [50:50<9:09:05,  1.47s/it]
  8%|▊         | 2049/24420 [50:52<9:09:38,  1.47s/it]
  8%|▊         | 2050/24420 [50:53<9:08:53,  1.47s/it]
                                                      
{'loss': 0.199, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2050/24420 [50:53<9:08:53,  1.47s/it]
  8%|▊         | 2051/24420 [50:55<9:08:41,  1.47s/it]
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  8%|▊         | 2055/24420 [51:00<9:09:46,  1.47s/it]
                                                      
{'loss': 0.2545, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2055/24420 [51:00<9:09:46,  1.47s/it]
  8%|▊         | 2056/24420 [51:02<9:10:02,  1.48s/it]
  8%|▊         | 2057/24420 [51:03<9:10:03,  1.48s/it]
  8%|▊         | 2058/24420 [51:05<9:09:14,  1.47s/it]
  8%|▊         | 2059/24420 [51:06<9:08:58,  1.47s/it]
  8%|▊         | 2060/24420 [51:08<9:09:37,  1.47s/it]
                                                      
{'loss': 0.226, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2060/24420 [51:08<9:09:37,  1.47s/it]
  8%|▊         | 2061/24420 [51:09<9:10:20,  1.48s/it]
  8%|▊         | 2062/24420 [51:11<9:09:12,  1.47s/it]
  8%|▊         | 2063/24420 [51:12<9:08:30,  1.47s/it]
  8%|▊         | 2064/24420 [51:14<9:08:04,  1.47s/it]
  8%|▊         | 2065/24420 [51:15<9:08:21,  1.47s/it]
                                                      
{'loss': 0.2383, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2065/24420 [51:15<9:08:21,  1.47s/it]
  8%|▊         | 2066/24420 [51:17<9:09:24,  1.47s/it]
  8%|▊         | 2067/24420 [51:18<9:08:40,  1.47s/it]
  8%|▊         | 2068/24420 [51:20<9:08:37,  1.47s/it]
  8%|▊         | 2069/24420 [51:21<9:09:02,  1.47s/it]
  8%|▊         | 2070/24420 [51:23<9:08:51,  1.47s/it]
                                                      
{'loss': 0.2271, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2070/24420 [51:23<9:08:51,  1.47s/it]
  8%|▊         | 2071/24420 [51:24<9:08:45,  1.47s/it]
  8%|▊         | 2072/24420 [51:26<9:11:51,  1.48s/it]
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  8%|▊         | 2074/24420 [51:28<9:10:36,  1.48s/it]
  8%|▊         | 2075/24420 [51:30<9:09:03,  1.47s/it]
                                                      
{'loss': 0.2322, 'learning_rate': 5e-05, 'epoch': 0.42}
+
  8%|▊         | 2075/24420 [51:30<9:09:03,  1.47s/it]
  9%|▊         | 2076/24420 [51:31<9:08:55,  1.47s/it]
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  9%|▊         | 2079/24420 [51:36<9:08:13,  1.47s/it]
  9%|▊         | 2080/24420 [51:37<9:08:34,  1.47s/it]
                                                      
{'loss': 0.2309, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2080/24420 [51:37<9:08:34,  1.47s/it]
  9%|▊         | 2081/24420 [51:39<9:14:23,  1.49s/it]
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  9%|▊         | 2084/24420 [51:43<9:09:18,  1.48s/it]
  9%|▊         | 2085/24420 [51:45<9:08:11,  1.47s/it]
                                                      
{'loss': 0.2177, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2085/24420 [51:45<9:08:11,  1.47s/it]
  9%|▊         | 2086/24420 [51:46<9:07:53,  1.47s/it]
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  9%|▊         | 2090/24420 [51:52<9:07:09,  1.47s/it]
                                                      
{'loss': 0.2384, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2090/24420 [51:52<9:07:09,  1.47s/it]
  9%|▊         | 2091/24420 [51:54<9:07:23,  1.47s/it]
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  9%|▊         | 2095/24420 [51:59<9:07:43,  1.47s/it]
                                                      
{'loss': 0.2221, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2095/24420 [51:59<9:07:43,  1.47s/it]
  9%|▊         | 2096/24420 [52:01<9:07:34,  1.47s/it]
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  9%|▊         | 2100/24420 [52:07<9:08:43,  1.48s/it]
                                                      
{'loss': 0.2085, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2100/24420 [52:07<9:08:43,  1.48s/it]
  9%|▊         | 2101/24420 [52:08<9:08:39,  1.47s/it]
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  9%|▊         | 2105/24420 [52:14<9:08:58,  1.48s/it]
                                                      
{'loss': 0.2133, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2105/24420 [52:14<9:08:58,  1.48s/it]
  9%|▊         | 2106/24420 [52:16<9:08:44,  1.48s/it]
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  9%|▊         | 2110/24420 [52:22<9:10:30,  1.48s/it]
                                                      
{'loss': 0.1812, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2110/24420 [52:22<9:10:30,  1.48s/it]
  9%|▊         | 2111/24420 [52:23<9:09:49,  1.48s/it]
  9%|▊         | 2112/24420 [52:25<9:08:54,  1.48s/it]
  9%|▊         | 2113/24420 [52:26<9:11:27,  1.48s/it]
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  9%|▊         | 2115/24420 [52:29<9:08:08,  1.47s/it]
                                                      
{'loss': 0.2018, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2115/24420 [52:29<9:08:08,  1.47s/it]
  9%|▊         | 2116/24420 [52:30<9:07:13,  1.47s/it]
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  9%|▊         | 2120/24420 [52:36<9:06:25,  1.47s/it]
                                                      
{'loss': 0.1914, 'learning_rate': 5e-05, 'epoch': 0.43}
+
  9%|▊         | 2120/24420 [52:36<9:06:25,  1.47s/it]
  9%|▊         | 2121/24420 [52:38<9:06:53,  1.47s/it]
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  9%|▊         | 2125/24420 [52:44<9:08:29,  1.48s/it]
                                                      
{'loss': 0.2328, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▊         | 2125/24420 [52:44<9:08:29,  1.48s/it]
  9%|▊         | 2126/24420 [52:45<9:08:25,  1.48s/it]
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  9%|▊         | 2130/24420 [52:51<9:06:38,  1.47s/it]
                                                      
{'loss': 0.21, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▊         | 2130/24420 [52:51<9:06:38,  1.47s/it]
  9%|▊         | 2131/24420 [52:53<9:07:11,  1.47s/it]
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  9%|▊         | 2135/24420 [52:58<9:06:33,  1.47s/it]
                                                      
{'loss': 0.2125, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▊         | 2135/24420 [52:58<9:06:33,  1.47s/it]
  9%|▊         | 2136/24420 [53:00<9:07:52,  1.48s/it]
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  9%|▉         | 2140/24420 [53:06<9:07:51,  1.48s/it]
                                                      
{'loss': 0.2499, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▉         | 2140/24420 [53:06<9:07:51,  1.48s/it]
  9%|▉         | 2141/24420 [53:07<9:07:45,  1.48s/it]
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  9%|▉         | 2145/24420 [53:13<9:08:13,  1.48s/it]
                                                      
{'loss': 0.231, 'learning_rate': 5e-05, 'epoch': 0.44}
+
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  9%|▉         | 2150/24420 [53:21<9:07:01,  1.47s/it]
                                                      
{'loss': 0.1945, 'learning_rate': 5e-05, 'epoch': 0.44}
+
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  9%|▉         | 2151/24420 [53:22<9:08:09,  1.48s/it]
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  9%|▉         | 2155/24420 [53:28<9:08:54,  1.48s/it]
                                                      
{'loss': 0.194, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▉         | 2155/24420 [53:28<9:08:54,  1.48s/it]
  9%|▉         | 2156/24420 [53:29<9:09:46,  1.48s/it]
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  9%|▉         | 2160/24420 [53:35<9:08:21,  1.48s/it]
                                                      
{'loss': 0.2733, 'learning_rate': 5e-05, 'epoch': 0.44}
+
  9%|▉         | 2160/24420 [53:35<9:08:21,  1.48s/it]
  9%|▉         | 2161/24420 [53:37<9:07:54,  1.48s/it]
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{'loss': 0.2614, 'learning_rate': 5e-05, 'epoch': 0.44}
+
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  9%|▉         | 2166/24420 [53:44<9:06:55,  1.47s/it]
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{'loss': 0.2294, 'learning_rate': 5e-05, 'epoch': 0.44}
+
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{'loss': 0.2179, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.2134, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.2143, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.1833, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.1786, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.2037, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.2546, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.2136, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.193, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.1837, 'learning_rate': 5e-05, 'epoch': 0.45}
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{'loss': 0.163, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.2013, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.194, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.2091, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.245, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.1865, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.2274, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.2017, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.1933, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.263, 'learning_rate': 5e-05, 'epoch': 0.46}
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{'loss': 0.2048, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2042, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2228, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2031, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.23, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2394, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2254, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2111, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2007, 'learning_rate': 5e-05, 'epoch': 0.47}
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{'loss': 0.2068, 'learning_rate': 5e-05, 'epoch': 0.48}
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{'loss': 0.2097, 'learning_rate': 5e-05, 'epoch': 0.48}
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{'loss': 0.2215, 'learning_rate': 5e-05, 'epoch': 0.48}
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{'loss': 0.2187, 'learning_rate': 5e-05, 'epoch': 0.48}
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{'loss': 0.2151, 'learning_rate': 5e-05, 'epoch': 0.48}
+
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{'loss': 0.2124, 'learning_rate': 5e-05, 'epoch': 0.48}
+
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{'loss': 0.2238, 'learning_rate': 5e-05, 'epoch': 0.48}
+
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{'loss': 0.2064, 'learning_rate': 5e-05, 'epoch': 0.48}
+
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{'loss': 0.1957, 'learning_rate': 5e-05, 'epoch': 0.48}
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{'loss': 0.2328, 'learning_rate': 5e-05, 'epoch': 0.49}
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{'loss': 0.2032, 'learning_rate': 5e-05, 'epoch': 0.49}
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{'loss': 0.2006, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.2159, 'learning_rate': 5e-05, 'epoch': 0.49}
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{'loss': 0.2156, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.2316, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.1959, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.2118, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.2246, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.1822, 'learning_rate': 5e-05, 'epoch': 0.49}
+
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{'loss': 0.191, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.2705, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.1936, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.2754, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.1977, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.2203, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.1959, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.1938, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.2013, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.1976, 'learning_rate': 5e-05, 'epoch': 0.5}
+
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{'loss': 0.2196, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.2443, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.2003, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.1977, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.2013, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.1952, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.1973, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.2158, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.1819, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.1937, 'learning_rate': 5e-05, 'epoch': 0.51}
+
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{'loss': 0.2034, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.2332, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.2181, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.2482, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.2018, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.1971, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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{'loss': 0.2121, 'learning_rate': 5e-05, 'epoch': 0.52}
+
 10%|█         | 2550/24420 [1:03:19<8:56:19,  1.47s/it]
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{'loss': 0.192, 'learning_rate': 5e-05, 'epoch': 0.52}
+
 10%|█         | 2555/24420 [1:03:26<8:56:22,  1.47s/it]
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{'loss': 0.1714, 'learning_rate': 5e-05, 'epoch': 0.52}
+
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 11%|█         | 2565/24420 [1:03:41<8:57:27,  1.48s/it]
                                                        
{'loss': 0.2039, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2565/24420 [1:03:41<8:57:27,  1.48s/it]
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 11%|█         | 2570/24420 [1:03:48<8:57:38,  1.48s/it]
                                                        
{'loss': 0.2117, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2570/24420 [1:03:48<8:57:38,  1.48s/it]
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 11%|█         | 2575/24420 [1:03:56<8:58:04,  1.48s/it]
                                                        
{'loss': 0.1964, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2575/24420 [1:03:56<8:58:04,  1.48s/it]
 11%|█         | 2576/24420 [1:03:57<8:59:40,  1.48s/it]
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 11%|█         | 2580/24420 [1:04:03<8:57:29,  1.48s/it]
                                                        
{'loss': 0.202, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2580/24420 [1:04:03<8:57:29,  1.48s/it]
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 11%|█         | 2585/24420 [1:04:10<8:57:37,  1.48s/it]
                                                        
{'loss': 0.2076, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2585/24420 [1:04:10<8:57:37,  1.48s/it]
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{'loss': 0.2033, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2590/24420 [1:04:18<8:55:21,  1.47s/it]
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 11%|█         | 2595/24420 [1:04:25<8:55:52,  1.47s/it]
                                                        
{'loss': 0.1841, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2595/24420 [1:04:25<8:55:52,  1.47s/it]
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 11%|█         | 2600/24420 [1:04:32<8:55:58,  1.47s/it]
                                                        
{'loss': 0.2035, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2600/24420 [1:04:32<8:55:58,  1.47s/it]
 11%|█         | 2601/24420 [1:04:37<14:47:53,  2.44s/it]
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 11%|█         | 2605/24420 [1:04:43<10:18:34,  1.70s/it]
                                                         
{'loss': 0.1899, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2605/24420 [1:04:43<10:18:34,  1.70s/it]
 11%|█         | 2606/24420 [1:04:44<9:53:35,  1.63s/it] 
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 11%|█         | 2610/24420 [1:04:50<9:10:40,  1.51s/it]
                                                        
{'loss': 0.1965, 'learning_rate': 5e-05, 'epoch': 0.53}
+
 11%|█         | 2610/24420 [1:04:50<9:10:40,  1.51s/it]
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 11%|█         | 2615/24420 [1:04:58<8:58:26,  1.48s/it]
                                                        
{'loss': 0.2158, 'learning_rate': 5e-05, 'epoch': 0.54}
+
 11%|█         | 2615/24420 [1:04:58<8:58:26,  1.48s/it]
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 11%|█         | 2620/24420 [1:05:05<8:55:42,  1.47s/it]
                                                        
{'loss': 0.2032, 'learning_rate': 5e-05, 'epoch': 0.54}
+
 11%|█         | 2620/24420 [1:05:05<8:55:42,  1.47s/it]
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{'loss': 0.1938, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.2155, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.2167, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.2153, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.2061, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.1823, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.2436, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.1748, 'learning_rate': 5e-05, 'epoch': 0.54}
+
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{'loss': 0.1882, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.2371, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1905, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1816, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1974, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1931, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1919, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1804, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1884, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.2267, 'learning_rate': 5e-05, 'epoch': 0.55}
+
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{'loss': 0.1781, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.1879, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.1758, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.2057, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.2455, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.225, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.1925, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.1949, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.1673, 'learning_rate': 5e-05, 'epoch': 0.56}
+
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{'loss': 0.213, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.2136, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.1728, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.1819, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.2287, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.1954, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.1893, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.198, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.214, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.235, 'learning_rate': 5e-05, 'epoch': 0.57}
+
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{'loss': 0.1768, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.185, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.185, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.1827, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.158, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.1609, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.1884, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.204, 'learning_rate': 5e-05, 'epoch': 0.58}
+
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{'loss': 0.1896, 'learning_rate': 5e-05, 'epoch': 0.58}
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{'loss': 0.2387, 'learning_rate': 5e-05, 'epoch': 0.58}
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{'loss': 0.1803, 'learning_rate': 5e-05, 'epoch': 0.59}
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{'loss': 0.1917, 'learning_rate': 5e-05, 'epoch': 0.59}
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{'loss': 0.1994, 'learning_rate': 5e-05, 'epoch': 0.59}
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{'loss': 0.1604, 'learning_rate': 5e-05, 'epoch': 0.59}
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{'loss': 0.181, 'learning_rate': 5e-05, 'epoch': 0.59}
+
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{'loss': 0.1846, 'learning_rate': 5e-05, 'epoch': 0.59}
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{'loss': 0.2133, 'learning_rate': 5e-05, 'epoch': 0.59}
+
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{'loss': 0.2052, 'learning_rate': 5e-05, 'epoch': 0.59}
+
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{'loss': 0.1713, 'learning_rate': 5e-05, 'epoch': 0.59}
+
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{'loss': 0.1929, 'learning_rate': 5e-05, 'epoch': 0.59}
+
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{'loss': 0.1848, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.1948, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.2016, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.1938, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.2089, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.1804, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.1814, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.2017, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.2203, 'learning_rate': 5e-05, 'epoch': 0.6}
+
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{'loss': 0.1658, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.169, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.1791, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.1835, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.1664, 'learning_rate': 5e-05, 'epoch': 0.61}
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{'loss': 0.1902, 'learning_rate': 5e-05, 'epoch': 0.61}
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{'loss': 0.1589, 'learning_rate': 5e-05, 'epoch': 0.61}
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{'loss': 0.1762, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.1808, 'learning_rate': 5e-05, 'epoch': 0.61}
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{'loss': 0.1814, 'learning_rate': 5e-05, 'epoch': 0.61}
+
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{'loss': 0.2258, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.1884, 'learning_rate': 5e-05, 'epoch': 0.62}
+
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{'loss': 0.2081, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.1662, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.2059, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.1843, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.2048, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.2003, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.1897, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.2069, 'learning_rate': 5e-05, 'epoch': 0.62}
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{'loss': 0.2012, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.2021, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.1808, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.203, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.2024, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.1765, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.164, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.1823, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.187, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.1967, 'learning_rate': 5e-05, 'epoch': 0.63}
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{'loss': 0.1535, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1764, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1872, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1694, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1769, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1973, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1604, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1909, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.152, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1772, 'learning_rate': 5e-05, 'epoch': 0.64}
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{'loss': 0.1799, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.183, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1694, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1812, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1873, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1935, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1738, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1678, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1607, 'learning_rate': 5e-05, 'epoch': 0.65}
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{'loss': 0.1747, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1914, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.181, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1738, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1913, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1616, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.2089, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1989, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1792, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.1985, 'learning_rate': 5e-05, 'epoch': 0.66}
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{'loss': 0.2211, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.195, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1881, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.2113, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1909, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1871, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1955, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1785, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1816, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.203, 'learning_rate': 5e-05, 'epoch': 0.67}
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{'loss': 0.1912, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.163, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.2034, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1909, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1708, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.174, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.2315, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1785, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1805, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1547, 'learning_rate': 5e-05, 'epoch': 0.68}
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{'loss': 0.1866, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1941, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1445, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1695, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1764, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.2209, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1793, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.2221, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.2049, 'learning_rate': 5e-05, 'epoch': 0.69}
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{'loss': 0.1704, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.1856, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.1675, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.181, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.1492, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.2022, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.1891, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.2519, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.2048, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.2191, 'learning_rate': 5e-05, 'epoch': 0.7}
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{'loss': 0.1792, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1804, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1647, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1985, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.167, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.2003, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1911, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1864, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1909, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.1788, 'learning_rate': 5e-05, 'epoch': 0.71}
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{'loss': 0.212, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1935, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1678, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1838, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1773, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1678, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1645, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1938, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.1788, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.168, 'learning_rate': 5e-05, 'epoch': 0.72}
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{'loss': 0.174, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1663, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1936, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1786, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1729, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1937, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.173, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1898, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1733, 'learning_rate': 5e-05, 'epoch': 0.73}
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{'loss': 0.1819, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1815, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.18, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.2057, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1724, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1488, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1971, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.203, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1689, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1868, 'learning_rate': 5e-05, 'epoch': 0.74}
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{'loss': 0.1621, 'learning_rate': 5e-05, 'epoch': 0.75}
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{'loss': 0.1781, 'learning_rate': 5e-05, 'epoch': 0.75}
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{'loss': 0.1892, 'learning_rate': 5e-05, 'epoch': 0.75}
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{'loss': 0.1528, 'learning_rate': 5e-05, 'epoch': 0.75}
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{'loss': 0.1681, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.1941, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.1651, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.1432, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.1683, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.2027, 'learning_rate': 5e-05, 'epoch': 0.75}
+
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{'loss': 0.1563, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1686, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1368, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1851, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1767, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1576, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1605, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1924, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1739, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.1592, 'learning_rate': 5e-05, 'epoch': 0.76}
+
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{'loss': 0.193, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1654, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1734, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1581, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1608, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1675, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1659, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1636, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.2285, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1508, 'learning_rate': 5e-05, 'epoch': 0.77}
+
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{'loss': 0.1645, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1669, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1886, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1734, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1617, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1711, 'learning_rate': 5e-05, 'epoch': 0.78}
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{'loss': 0.1799, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1745, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.1444, 'learning_rate': 5e-05, 'epoch': 0.78}
+
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{'loss': 0.168, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.2005, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1917, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1812, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.2068, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1633, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1693, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1522, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1652, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.129, 'learning_rate': 5e-05, 'epoch': 0.79}
+
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{'loss': 0.1577, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1713, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.168, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1623, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1579, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1616, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1962, 'learning_rate': 5e-05, 'epoch': 0.8}
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{'loss': 0.1702, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1787, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1819, 'learning_rate': 5e-05, 'epoch': 0.8}
+
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{'loss': 0.1675, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1689, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1565, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1628, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1698, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1674, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.2163, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1615, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.1699, 'learning_rate': 5e-05, 'epoch': 0.81}
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{'loss': 0.168, 'learning_rate': 5e-05, 'epoch': 0.81}
+
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{'loss': 0.1607, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1675, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.16, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1672, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1531, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1895, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1576, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1747, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.1727, 'learning_rate': 5e-05, 'epoch': 0.82}
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{'loss': 0.2049, 'learning_rate': 5e-05, 'epoch': 0.83}
+
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{'loss': 0.1779, 'learning_rate': 5e-05, 'epoch': 0.83}
+
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{'loss': 0.1878, 'learning_rate': 5e-05, 'epoch': 0.83}
+
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{'loss': 0.1658, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1975, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1697, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1683, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1821, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1789, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1703, 'learning_rate': 5e-05, 'epoch': 0.83}
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{'loss': 0.1786, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1354, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1681, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1679, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.164, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1603, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.17, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1506, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1629, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1695, 'learning_rate': 5e-05, 'epoch': 0.84}
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{'loss': 0.1344, 'learning_rate': 5e-05, 'epoch': 0.85}
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{'loss': 0.1462, 'learning_rate': 5e-05, 'epoch': 0.85}
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{'loss': 0.1561, 'learning_rate': 5e-05, 'epoch': 0.85}
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{'loss': 0.1977, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1563, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1512, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1683, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1865, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1832, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1778, 'learning_rate': 5e-05, 'epoch': 0.85}
+
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{'loss': 0.1756, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1435, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1648, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1811, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1585, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.2436, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1744, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1697, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.1407, 'learning_rate': 5e-05, 'epoch': 0.86}
+
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{'loss': 0.2023, 'learning_rate': 5e-05, 'epoch': 0.87}
+
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{'loss': 0.1711, 'learning_rate': 5e-05, 'epoch': 0.87}
+
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{'loss': 0.1521, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1725, 'learning_rate': 5e-05, 'epoch': 0.87}
+
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{'loss': 0.1527, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1742, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1772, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1786, 'learning_rate': 5e-05, 'epoch': 0.87}
+
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{'loss': 0.1968, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1455, 'learning_rate': 5e-05, 'epoch': 0.87}
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{'loss': 0.1532, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1697, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1509, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1375, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1823, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1701, 'learning_rate': 5e-05, 'epoch': 0.88}
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{'loss': 0.1706, 'learning_rate': 5e-05, 'epoch': 0.88}
+
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{'loss': 0.1574, 'learning_rate': 5e-05, 'epoch': 0.88}
+
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{'loss': 0.1497, 'learning_rate': 5e-05, 'epoch': 0.88}
+
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{'loss': 0.1415, 'learning_rate': 5e-05, 'epoch': 0.88}
+
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{'loss': 0.1462, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1608, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.166, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1482, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1996, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1792, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1503, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1548, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1702, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1525, 'learning_rate': 5e-05, 'epoch': 0.89}
+
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{'loss': 0.1485, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1792, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1599, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1554, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1744, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1672, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.174, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.163, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1516, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.152, 'learning_rate': 5e-05, 'epoch': 0.9}
+
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{'loss': 0.1536, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1527, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1297, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1703, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1705, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1558, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1434, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.1913, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.155, 'learning_rate': 5e-05, 'epoch': 0.91}
+
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{'loss': 0.145, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1288, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1879, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1461, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1622, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1604, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1574, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1321, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1865, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1329, 'learning_rate': 5e-05, 'epoch': 0.92}
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{'loss': 0.1742, 'learning_rate': 5e-05, 'epoch': 0.93}
+
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{'loss': 0.1518, 'learning_rate': 5e-05, 'epoch': 0.93}
+
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{'loss': 0.18, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1661, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1559, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.188, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1841, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1448, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1752, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1631, 'learning_rate': 5e-05, 'epoch': 0.93}
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{'loss': 0.1358, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.159, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.164, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1516, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1449, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1428, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1588, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1519, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1363, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1737, 'learning_rate': 5e-05, 'epoch': 0.94}
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{'loss': 0.1529, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1549, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1769, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1508, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1971, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.2165, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1646, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1258, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1516, 'learning_rate': 5e-05, 'epoch': 0.95}
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{'loss': 0.1545, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1618, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1394, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1821, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1325, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1728, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1421, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.181, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1586, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1419, 'learning_rate': 5e-05, 'epoch': 0.96}
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{'loss': 0.1609, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1347, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.135, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1423, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1613, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1567, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1419, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1526, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1518, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1328, 'learning_rate': 5e-05, 'epoch': 0.97}
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{'loss': 0.1449, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1412, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1179, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1574, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1593, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1813, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1521, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1584, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1555, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.167, 'learning_rate': 5e-05, 'epoch': 0.98}
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{'loss': 0.1485, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1367, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1462, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1569, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1564, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1449, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1469, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.135, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.145, 'learning_rate': 5e-05, 'epoch': 0.99}
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{'loss': 0.1447, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1586, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1531, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.157, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1516, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1331, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1364, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1379, 'learning_rate': 5e-05, 'epoch': 1.0}
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{'loss': 0.1451, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1574, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1633, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1497, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1301, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1648, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1471, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1306, 'learning_rate': 5e-05, 'epoch': 1.01}
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{'loss': 0.1463, 'learning_rate': 5e-05, 'epoch': 1.08}
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{'loss': 0.1141, 'learning_rate': 5e-05, 'epoch': 1.08}
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{'loss': 0.146, 'learning_rate': 5e-05, 'epoch': 1.08}
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{'loss': 0.1381, 'learning_rate': 5e-05, 'epoch': 1.08}
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{'loss': 0.1441, 'learning_rate': 5e-05, 'epoch': 1.08}
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{'loss': 0.1307, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.1455, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.1308, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.1472, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.119, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.1299, 'learning_rate': 5e-05, 'epoch': 1.09}
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{'loss': 0.128, 'learning_rate': 5e-05, 'epoch': 1.1}
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{'loss': 0.1235, 'learning_rate': 5e-05, 'epoch': 1.11}
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{'loss': 0.1453, 'learning_rate': 5e-05, 'epoch': 1.11}
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{'loss': 0.1566, 'learning_rate': 5e-05, 'epoch': 1.11}
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{'loss': 0.1726, 'learning_rate': 5e-05, 'epoch': 1.11}
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{'loss': 0.1428, 'learning_rate': 5e-05, 'epoch': 1.11}
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{'loss': 0.125, 'learning_rate': 5e-05, 'epoch': 1.15}
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{'loss': 0.1344, 'learning_rate': 5e-05, 'epoch': 1.16}
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{'loss': 0.1142, 'learning_rate': 5e-05, 'epoch': 1.16}
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{'loss': 0.115, 'learning_rate': 5e-05, 'epoch': 1.17}
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{'loss': 0.1382, 'learning_rate': 5e-05, 'epoch': 1.17}
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{'loss': 0.1496, 'learning_rate': 5e-05, 'epoch': 1.17}
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{'loss': 0.1359, 'learning_rate': 5e-05, 'epoch': 1.17}
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{'loss': 0.1301, 'learning_rate': 5e-05, 'epoch': 1.17}
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{'loss': 0.1472, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.1298, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.141, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.1281, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.1498, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.1286, 'learning_rate': 5e-05, 'epoch': 1.18}
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{'loss': 0.1323, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1133, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1195, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1455, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1368, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1262, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.1341, 'learning_rate': 5e-05, 'epoch': 1.21}
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{'loss': 0.126, 'learning_rate': 5e-05, 'epoch': 1.41}
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{'loss': 0.1022, 'learning_rate': 5e-05, 'epoch': 1.51}
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{'loss': 0.1017, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1336, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1348, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1298, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1031, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1647, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.0953, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1137, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1174, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1157, 'learning_rate': 5e-05, 'epoch': 1.52}
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{'loss': 0.1128, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1059, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1214, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1214, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1105, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1308, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.125, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.134, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.0948, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1139, 'learning_rate': 5e-05, 'epoch': 1.53}
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{'loss': 0.1159, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1333, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1184, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.0958, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1107, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1183, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1222, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1247, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1407, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1172, 'learning_rate': 5e-05, 'epoch': 1.54}
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{'loss': 0.1106, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1234, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1306, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.114, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1126, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1186, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1238, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1313, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1188, 'learning_rate': 5e-05, 'epoch': 1.55}
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{'loss': 0.1135, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1311, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1247, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1126, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1111, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.108, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1115, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.092, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1031, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1066, 'learning_rate': 5e-05, 'epoch': 1.56}
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{'loss': 0.1057, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1074, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1161, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1147, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1142, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1139, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.107, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1297, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1256, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1216, 'learning_rate': 5e-05, 'epoch': 1.57}
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{'loss': 0.1294, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1122, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1087, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1054, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1222, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.176, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1421, 'learning_rate': 5e-05, 'epoch': 1.58}
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{'loss': 0.1176, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1069, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1183, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1225, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.098, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1054, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1227, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.121, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1005, 'learning_rate': 5e-05, 'epoch': 1.59}
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{'loss': 0.1077, 'learning_rate': 5e-05, 'epoch': 1.6}
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{'loss': 0.1044, 'learning_rate': 5e-05, 'epoch': 1.6}
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{'loss': 0.1092, 'learning_rate': 5e-05, 'epoch': 1.61}
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{'loss': 0.1117, 'learning_rate': 5e-05, 'epoch': 1.61}
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{'loss': 0.132, 'learning_rate': 5e-05, 'epoch': 1.81}
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{'loss': 0.102, 'learning_rate': 5e-05, 'epoch': 1.81}
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{'loss': 0.1051, 'learning_rate': 5e-05, 'epoch': 1.81}
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{'loss': 0.1113, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1221, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1271, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1164, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1126, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1131, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.113, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1002, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.1238, 'learning_rate': 5e-05, 'epoch': 1.82}
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{'loss': 0.115, 'learning_rate': 5e-05, 'epoch': 1.83}
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{'loss': 0.0864, 'learning_rate': 5e-05, 'epoch': 1.83}
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{'loss': 0.0971, 'learning_rate': 5e-05, 'epoch': 1.84}
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{'loss': 0.0952, 'learning_rate': 5e-05, 'epoch': 1.84}
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{'loss': 0.1198, 'learning_rate': 5e-05, 'epoch': 1.84}
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{'loss': 0.1116, 'learning_rate': 5e-05, 'epoch': 1.84}
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{'loss': 0.1161, 'learning_rate': 5e-05, 'epoch': 1.86}
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{'loss': 0.1108, 'learning_rate': 5e-05, 'epoch': 1.86}
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{'loss': 0.109, 'learning_rate': 5e-05, 'epoch': 1.87}
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{'loss': 0.0938, 'learning_rate': 5e-05, 'epoch': 1.87}
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{'loss': 0.0997, 'learning_rate': 5e-05, 'epoch': 1.87}
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{'loss': 0.113, 'learning_rate': 5e-05, 'epoch': 1.9}
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{'loss': 0.0987, 'learning_rate': 5e-05, 'epoch': 2.07}
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{'loss': 0.1017, 'learning_rate': 5e-05, 'epoch': 2.07}
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{'loss': 0.0951, 'learning_rate': 5e-05, 'epoch': 2.07}
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{'loss': 0.0963, 'learning_rate': 5e-05, 'epoch': 2.08}
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{'loss': 0.1003, 'learning_rate': 5e-05, 'epoch': 2.08}
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{'loss': 0.0916, 'learning_rate': 5e-05, 'epoch': 2.09}
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{'loss': 0.1123, 'learning_rate': 5e-05, 'epoch': 2.09}
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{'loss': 0.092, 'learning_rate': 5e-05, 'epoch': 2.09}
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{'loss': 0.0999, 'learning_rate': 5e-05, 'epoch': 2.1}
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{'loss': 0.091, 'learning_rate': 5e-05, 'epoch': 2.11}
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{'loss': 0.089, 'learning_rate': 5e-05, 'epoch': 2.12}
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{'loss': 0.0806, 'learning_rate': 5e-05, 'epoch': 2.14}
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{'loss': 0.1008, 'learning_rate': 5e-05, 'epoch': 2.19}
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{'loss': 0.084, 'learning_rate': 5e-05, 'epoch': 2.21}
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{'loss': 0.1177, 'learning_rate': 5e-05, 'epoch': 2.22}
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{'loss': 0.101, 'learning_rate': 5e-05, 'epoch': 2.22}
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{'loss': 0.1169, 'learning_rate': 5e-05, 'epoch': 2.23}
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{'loss': 0.089, 'learning_rate': 5e-05, 'epoch': 2.23}
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{'loss': 0.1163, 'learning_rate': 5e-05, 'epoch': 2.23}
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{'loss': 0.1242, 'learning_rate': 5e-05, 'epoch': 2.23}
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{'loss': 0.0986, 'learning_rate': 5e-05, 'epoch': 2.26}
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{'loss': 0.1163, 'learning_rate': 5e-05, 'epoch': 2.27}
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{'loss': 0.0838, 'learning_rate': 5e-05, 'epoch': 2.27}
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{'loss': 0.0702, 'learning_rate': 5e-05, 'epoch': 2.27}
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{'loss': 0.0973, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.097, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0879, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.081, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0839, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0886, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0954, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0795, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.0801, 'learning_rate': 5e-05, 'epoch': 2.28}
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{'loss': 0.1086, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0881, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0993, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.083, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0917, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.1024, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0873, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0789, 'learning_rate': 5e-05, 'epoch': 2.29}
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{'loss': 0.0937, 'learning_rate': 5e-05, 'epoch': 2.42}
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{'loss': 0.0978, 'learning_rate': 5e-05, 'epoch': 2.43}
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{'loss': 0.0827, 'learning_rate': 5e-05, 'epoch': 2.43}
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{'loss': 0.092, 'learning_rate': 5e-05, 'epoch': 2.43}
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{'loss': 0.0978, 'learning_rate': 5e-05, 'epoch': 2.43}
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{'loss': 0.0798, 'learning_rate': 5e-05, 'epoch': 2.43}
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{'loss': 0.0869, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0888, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0832, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0973, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0994, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0999, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.084, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0934, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0985, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0901, 'learning_rate': 5e-05, 'epoch': 2.44}
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{'loss': 0.0985, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0921, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0744, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0697, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.1333, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0859, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0947, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0934, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.1026, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0855, 'learning_rate': 5e-05, 'epoch': 2.45}
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{'loss': 0.0953, 'learning_rate': 5e-05, 'epoch': 2.46}
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{'loss': 0.0942, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.0885, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.1057, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.092, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.0951, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.0862, 'learning_rate': 5e-05, 'epoch': 2.47}
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{'loss': 0.1028, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0983, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.1103, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0842, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0878, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0919, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.1118, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0884, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.0789, 'learning_rate': 5e-05, 'epoch': 2.48}
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{'loss': 0.098, 'learning_rate': 5e-05, 'epoch': 2.49}
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{'loss': 0.0959, 'learning_rate': 5e-05, 'epoch': 2.49}
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{'loss': 0.0764, 'learning_rate': 5e-05, 'epoch': 2.49}
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{'loss': 0.1037, 'learning_rate': 5e-05, 'epoch': 2.49}
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{'loss': 0.0828, 'learning_rate': 5e-05, 'epoch': 2.92}
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{'loss': 0.0791, 'learning_rate': 5e-05, 'epoch': 3.02}
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{'loss': 0.0888, 'learning_rate': 5e-05, 'epoch': 3.02}
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{'loss': 0.085, 'learning_rate': 5e-05, 'epoch': 3.03}
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{'loss': 0.078, 'learning_rate': 5e-05, 'epoch': 3.03}
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{'loss': 0.1064, 'learning_rate': 5e-05, 'epoch': 3.03}
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{'loss': 0.0885, 'learning_rate': 5e-05, 'epoch': 3.03}
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{'loss': 0.0836, 'learning_rate': 5e-05, 'epoch': 3.03}
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{'loss': 0.0829, 'learning_rate': 5e-05, 'epoch': 3.04}
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{'loss': 0.1276, 'learning_rate': 5e-05, 'epoch': 3.04}
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{'loss': 0.077, 'learning_rate': 5e-05, 'epoch': 3.04}
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{'loss': 0.087, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.0773, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.074, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.0735, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.0945, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.0792, 'learning_rate': 5e-05, 'epoch': 3.05}
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{'loss': 0.091, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0827, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0782, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0719, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0716, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0852, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0751, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0803, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.0812, 'learning_rate': 5e-05, 'epoch': 3.06}
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{'loss': 0.1016, 'learning_rate': 5e-05, 'epoch': 3.16}
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{'loss': 0.0812, 'learning_rate': 5e-05, 'epoch': 3.18}
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{'loss': 0.0788, 'learning_rate': 5e-05, 'epoch': 3.19}
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{'loss': 0.0758, 'learning_rate': 5e-05, 'epoch': 3.19}
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{'loss': 0.1038, 'learning_rate': 5e-05, 'epoch': 3.19}
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{'loss': 0.092, 'learning_rate': 5e-05, 'epoch': 3.19}
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{'loss': 0.0754, 'learning_rate': 5e-05, 'epoch': 3.19}
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{'loss': 0.0766, 'learning_rate': 5e-05, 'epoch': 3.25}
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{'loss': 0.0761, 'learning_rate': 5e-05, 'epoch': 3.32}
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{'loss': 0.0839, 'learning_rate': 5e-05, 'epoch': 3.44}
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{'loss': 0.077, 'learning_rate': 5e-05, 'epoch': 3.47}
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{'loss': 0.0731, 'learning_rate': 5e-05, 'epoch': 3.47}
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{'loss': 0.075, 'learning_rate': 5e-05, 'epoch': 3.47}
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{'loss': 0.0758, 'learning_rate': 5e-05, 'epoch': 3.47}
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{'loss': 0.0707, 'learning_rate': 5e-05, 'epoch': 3.48}
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{'loss': 0.0874, 'learning_rate': 5e-05, 'epoch': 3.54}
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{'loss': 0.0722, 'learning_rate': 5e-05, 'epoch': 3.59}
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{'loss': 0.07, 'learning_rate': 5e-05, 'epoch': 3.59}
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{'loss': 0.0818, 'learning_rate': 5e-05, 'epoch': 3.63}
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{'loss': 0.081, 'learning_rate': 5e-05, 'epoch': 3.63}
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{'loss': 0.079, 'learning_rate': 5e-05, 'epoch': 3.65}
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{'loss': 0.0867, 'learning_rate': 5e-05, 'epoch': 3.66}
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{'loss': 0.0753, 'learning_rate': 5e-05, 'epoch': 3.66}
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{'loss': 0.0737, 'learning_rate': 5e-05, 'epoch': 3.67}
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{'loss': 0.0731, 'learning_rate': 5e-05, 'epoch': 3.8}
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{'loss': 0.0926, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.0869, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.0865, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.0696, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.075, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.0867, 'learning_rate': 5e-05, 'epoch': 3.85}
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{'loss': 0.062, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0684, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0711, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0896, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0757, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0863, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0745, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.1053, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0725, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.076, 'learning_rate': 5e-05, 'epoch': 3.86}
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{'loss': 0.0976, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0709, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0763, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0818, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0818, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0805, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.063, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.1042, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0941, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0733, 'learning_rate': 5e-05, 'epoch': 3.87}
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{'loss': 0.0826, 'learning_rate': 5e-05, 'epoch': 3.88}
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{'loss': 0.0724, 'learning_rate': 5e-05, 'epoch': 3.88}
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{'loss': 0.0816, 'learning_rate': 5e-05, 'epoch': 3.88}
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{'loss': 0.075, 'learning_rate': 5e-05, 'epoch': 3.91}
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{'loss': 0.0659, 'learning_rate': 5e-05, 'epoch': 3.91}
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{'loss': 0.0665, 'learning_rate': 5e-05, 'epoch': 3.91}
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{'loss': 0.088, 'learning_rate': 5e-05, 'epoch': 3.91}
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{'loss': 0.0834, 'learning_rate': 5e-05, 'epoch': 3.91}
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{'loss': 0.0911, 'learning_rate': 5e-05, 'epoch': 3.92}
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{'loss': 0.0761, 'learning_rate': 5e-05, 'epoch': 3.93}
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{'loss': 0.0679, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.0712, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.0749, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.0664, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.067, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.0692, 'learning_rate': 5e-05, 'epoch': 4.04}
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{'loss': 0.0828, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0737, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.066, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0773, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0834, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0664, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0918, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0652, 'learning_rate': 5e-05, 'epoch': 4.05}
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{'loss': 0.0976, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.081, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.0659, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.0667, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.0674, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.081, 'learning_rate': 5e-05, 'epoch': 4.06}
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{'loss': 0.0681, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0747, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0847, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.069, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0751, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0613, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.08, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0724, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0704, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0706, 'learning_rate': 5e-05, 'epoch': 4.07}
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{'loss': 0.0678, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0698, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0651, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0663, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.089, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0743, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.067, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0701, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0793, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0686, 'learning_rate': 5e-05, 'epoch': 4.08}
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{'loss': 0.0862, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0693, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0678, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0691, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.055, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0711, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0788, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0701, 'learning_rate': 5e-05, 'epoch': 4.09}
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{'loss': 0.0719, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.073, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0657, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0696, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0816, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0782, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0766, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0755, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0782, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0646, 'learning_rate': 5e-05, 'epoch': 4.1}
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{'loss': 0.0616, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0747, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0778, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0736, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0552, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0809, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0641, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0775, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0741, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0798, 'learning_rate': 5e-05, 'epoch': 4.11}
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{'loss': 0.0766, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0697, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0781, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0781, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0821, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0638, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0812, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0812, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0774, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.12}
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{'loss': 0.0733, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.065, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0858, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0881, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0751, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0854, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0745, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0767, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0683, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0909, 'learning_rate': 5e-05, 'epoch': 4.13}
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{'loss': 0.0707, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0789, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0828, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0638, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0712, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0668, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.085, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0683, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0713, 'learning_rate': 5e-05, 'epoch': 4.14}
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{'loss': 0.0696, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0752, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.072, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0771, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0571, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0721, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0828, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0619, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0684, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.07, 'learning_rate': 5e-05, 'epoch': 4.15}
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{'loss': 0.0869, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0664, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0769, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0769, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0711, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0702, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0904, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0856, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0722, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.0676, 'learning_rate': 5e-05, 'epoch': 4.16}
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{'loss': 0.078, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.06, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0921, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0672, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0789, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0713, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0785, 'learning_rate': 5e-05, 'epoch': 4.17}
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{'loss': 0.0669, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0731, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0776, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0914, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0772, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0794, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0681, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0663, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0711, 'learning_rate': 5e-05, 'epoch': 4.18}
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{'loss': 0.0792, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0713, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0729, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0638, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0734, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0644, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0716, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0712, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0644, 'learning_rate': 5e-05, 'epoch': 4.19}
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{'loss': 0.0746, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0752, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0816, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0739, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0742, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0791, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0746, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0581, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0742, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0632, 'learning_rate': 5e-05, 'epoch': 4.2}
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{'loss': 0.0918, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0654, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0697, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0649, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0646, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0771, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.067, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0674, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0781, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0842, 'learning_rate': 5e-05, 'epoch': 4.21}
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{'loss': 0.0811, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0723, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0666, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0732, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.061, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.09, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0633, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0669, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0822, 'learning_rate': 5e-05, 'epoch': 4.22}
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{'loss': 0.0718, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.072, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.0791, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.0687, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.0772, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.069, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.0793, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.072, 'learning_rate': 5e-05, 'epoch': 4.23}
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{'loss': 0.0674, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.077, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.071, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0839, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0676, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0709, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0769, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0757, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0758, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0757, 'learning_rate': 5e-05, 'epoch': 4.24}
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{'loss': 0.0649, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0832, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0839, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0566, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0705, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0789, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0787, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0903, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0693, 'learning_rate': 5e-05, 'epoch': 4.25}
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{'loss': 0.0694, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0851, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0849, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0799, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0752, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0801, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.082, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0643, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.067, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0632, 'learning_rate': 5e-05, 'epoch': 4.26}
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{'loss': 0.0829, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0806, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0783, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0742, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.077, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0887, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0697, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0724, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0677, 'learning_rate': 5e-05, 'epoch': 4.27}
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{'loss': 0.0762, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0671, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0924, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0777, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0803, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0813, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.091, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0803, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.071, 'learning_rate': 5e-05, 'epoch': 4.28}
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{'loss': 0.0715, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0804, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0851, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0673, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0716, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0706, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0649, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0757, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0626, 'learning_rate': 5e-05, 'epoch': 4.29}
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{'loss': 0.0687, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0579, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0986, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0759, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0772, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0704, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0815, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0704, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0794, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0843, 'learning_rate': 5e-05, 'epoch': 4.3}
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{'loss': 0.0674, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0836, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0616, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0754, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0692, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0768, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0631, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0881, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0798, 'learning_rate': 5e-05, 'epoch': 4.31}
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{'loss': 0.0802, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0611, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0618, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.069, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0731, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0656, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0661, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0721, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0724, 'learning_rate': 5e-05, 'epoch': 4.32}
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{'loss': 0.0718, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0778, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0781, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0661, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0733, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0672, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0722, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0675, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0929, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.061, 'learning_rate': 5e-05, 'epoch': 4.33}
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{'loss': 0.0776, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0706, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0751, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0691, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.07, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0809, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0636, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0706, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0758, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.069, 'learning_rate': 5e-05, 'epoch': 4.34}
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{'loss': 0.0656, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0943, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0715, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0832, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0676, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0716, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0681, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.076, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0773, 'learning_rate': 5e-05, 'epoch': 4.35}
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{'loss': 0.0794, 'learning_rate': 5e-05, 'epoch': 4.36}
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{'loss': 0.0734, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.1013, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.0708, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.0665, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.0865, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.0683, 'learning_rate': 5e-05, 'epoch': 4.37}
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{'loss': 0.0715, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.073, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0808, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.067, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0746, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0792, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0752, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0678, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.071, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0855, 'learning_rate': 5e-05, 'epoch': 4.38}
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{'loss': 0.0763, 'learning_rate': 5e-05, 'epoch': 4.39}
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{'loss': 0.0798, 'learning_rate': 5e-05, 'epoch': 4.41}
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{'loss': 0.0744, 'learning_rate': 5e-05, 'epoch': 4.41}
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{'loss': 0.0685, 'learning_rate': 5e-05, 'epoch': 4.42}
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{'loss': 0.0875, 'learning_rate': 5e-05, 'epoch': 4.42}
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{'loss': 0.0774, 'learning_rate': 5e-05, 'epoch': 4.42}
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{'loss': 0.0733, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0604, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.07, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0675, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0658, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0808, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0661, 'learning_rate': 5e-05, 'epoch': 4.44}
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{'loss': 0.0624, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.0802, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.0756, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.0744, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.08, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.065, 'learning_rate': 5e-05, 'epoch': 4.45}
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{'loss': 0.072, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.076, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0773, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0657, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0645, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0753, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0764, 'learning_rate': 5e-05, 'epoch': 4.46}
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{'loss': 0.0719, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0707, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0614, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.077, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0896, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0801, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0695, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0724, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0705, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0726, 'learning_rate': 5e-05, 'epoch': 4.47}
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{'loss': 0.0703, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.1047, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.0807, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.0703, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.0787, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.07, 'learning_rate': 5e-05, 'epoch': 4.48}
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{'loss': 0.0681, 'learning_rate': 5e-05, 'epoch': 4.99}
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{'loss': 0.0654, 'learning_rate': 5e-05, 'epoch': 5.0}
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{'loss': 0.0926, 'learning_rate': 5e-05, 'epoch': 5.0}
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{'loss': 0.0682, 'learning_rate': 5e-05, 'epoch': 5.0}
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{'loss': 0.0853, 'learning_rate': 5e-05, 'epoch': 5.0}
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{'loss': 0.0634, 'learning_rate': 5e-05, 'epoch': 5.0}
+
100%|██████████| 24420/24420 [10:12:03<00:00,  1.49s/it]Time: 36724.34
+Samples/second: 15.96
+
                                                        
Time: 36724.34{'train_runtime': 36723.963, 'train_samples_per_second': 15.961, 'train_steps_per_second': 0.665, 'train_loss': 0.12059639945784911, 'epoch': 5.0}
+
+Samples/second: 15.96
+
100%|██████████| 24420/24420 [10:12:03<00:00,  1.49s/it]GPU memory occupied: 47582 MB.
+GPU memory occupied: 47582 MB.
+
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+Time: 36723.96
+Samples/second: 15.96
+GPU memory occupied: 47582 MB.
+Time: 36724.47
+Samples/second: 15.96
+GPU memory occupied: 47582 MB.
+[2022-12-21 03:32:45,648] [INFO] [launch.py:350:main] Process 2267 exits successfully.
+[2022-12-21 03:32:46,650] [INFO] [launch.py:350:main] Process 2269 exits successfully.
+[2022-12-21 03:32:46,650] [INFO] [launch.py:350:main] Process 2270 exits successfully.
+[2022-12-21 03:32:46,652] [INFO] [launch.py:350:main] Process 2268 exits successfully.