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encode-chrombpnet-DNASE-ENCSR108SYM-ENCSR705JPE

chrombpnet
encode
chromatin-accessibility
DNASE
muscle
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +3 -0
  2. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.bias_formatting.stdout.txt +1 -0
  4. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.chrombpnet.params.json +11 -0
  5. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.chrombpnet_formatting.stdout.txt +1 -0
  6. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.stdout_v1.txt +3 -0
  9. fold_0/model.bias_scaled.fold_0.ENCSR108SYM.h5 +3 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR108SYM.tar +3 -0
  11. fold_0/model.chrombpnet.fold_0.ENCSR108SYM.h5 +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR108SYM.tar +3 -0
  13. fold_0/model.chrombpnet_nobias.fold_0.ENCSR108SYM.h5 +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR108SYM.tar +3 -0
  15. fold_1/model.bias_scaled.fold_1.ENCSR108SYM.h5 +3 -0
  16. fold_1/model.bias_scaled.fold_1.ENCSR108SYM.tar +3 -0
  17. fold_1/model.chrombpnet.fold_1.ENCSR108SYM.h5 +3 -0
  18. fold_1/model.chrombpnet.fold_1.ENCSR108SYM.tar +3 -0
  19. fold_1/model.chrombpnet_nobias.fold_1.ENCSR108SYM.h5 +3 -0
  20. fold_1/model.chrombpnet_nobias.fold_1.ENCSR108SYM.tar +3 -0
  21. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.args.json +23 -0
  22. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.batch_loss.tsv +0 -0
  23. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.bias_formatting.stderr.txt +38 -0
  24. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.bias_formatting.stdout.txt +1 -0
  25. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet.params.json +11 -0
  26. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_data_params.tsv +3 -0
  27. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_formatting.stderr.txt +40 -0
  28. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_formatting.stdout.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_model_params.tsv +9 -0
  30. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  31. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.epoch_loss.csv +12 -0
  33. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.stderr.txt +0 -0
  34. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.stdout.txt +0 -0
  35. fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.stdout_v1.txt +0 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR108SYM.h5 +3 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR108SYM.tar +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR108SYM.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR108SYM.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR108SYM.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR108SYM.tar +3 -0
  42. fold_3/model.bias_scaled.fold_3.ENCSR108SYM.h5 +3 -0
  43. fold_3/model.bias_scaled.fold_3.ENCSR108SYM.tar +3 -0
  44. fold_3/model.chrombpnet.fold_3.ENCSR108SYM.h5 +3 -0
  45. fold_3/model.chrombpnet.fold_3.ENCSR108SYM.tar +3 -0
  46. fold_3/model.chrombpnet_nobias.fold_3.ENCSR108SYM.h5 +3 -0
  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR108SYM.tar +3 -0
  48. fold_4/logs.models.fold_4.ENCSR108SYM/logfile.modelling.fold_4.ENCSR108SYM.stdout.txt +3 -0
  49. fold_4/logs.models.fold_4.ENCSR108SYM/logfile.modelling.fold_4.ENCSR108SYM.stdout_v1.txt +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR108SYM.h5 +3 -0
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fold_0/logs.models.fold_0.ENCSR108SYM/logfile.modelling.fold_0.ENCSR108SYM.bias_formatting.stdout.txt ADDED
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+ 2023-07-15 02:33:29.849219: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-15 02:33:29.853211: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-15 02:33:29.882488: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
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+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
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+ 2023-07-15 02:33:29.882566: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:29.946988: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:33:29.953041: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:33:29.954202: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:33:29.955941: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-15 02:33:29.956328: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
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+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
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+ 2023-07-15 02:33:29.957330: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-15 02:33:29.957598: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
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+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
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+ 2023-07-15 02:33:29.957629: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:29.957653: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-15 02:33:29.957675: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-15 02:33:29.957696: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:33:29.957718: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:33:29.957738: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:33:29.957759: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:33:29.957780: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:33:29.958157: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-15 02:33:29.959453: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 02:33:31.809687: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 02:33:31.809781: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 02:33:31.809799: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 02:33:31.812695: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14957 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:04:00.0, compute capability: 6.0)
38
+ 2023-07-15 02:33:32.713453: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR108SYM//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR108SYM//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
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3
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4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR108SYM//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5",
6
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7
+ "outputlen": "1000",
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9
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 12.0
2
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3
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fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 01:31:17.685906: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 01:31:20.089025: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
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6
+ 2023-07-15 01:31:21.019456: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-15 01:31:21.019531: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
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11
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12
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13
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14
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15
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16
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17
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18
+ 2023-07-15 01:31:21.083717: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
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21
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22
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-15 01:31:21.090504: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 01:31:21.090535: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
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27
+ 2023-07-15 01:31:21.090582: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 01:31:21.090603: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 01:31:21.090623: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
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31
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32
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33
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34
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35
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36
+ 2023-07-15 01:31:23.609173: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 01:31:23.654358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
38
+ 2023-07-15 01:31:25.838673: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
39
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
40
+ , UserWarning)
fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
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fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 25.2
2
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3
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4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR108SYM//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5
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fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_no_bias_formatting.stderr.txt ADDED
@@ -0,0 +1 @@
 
 
1
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fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.chrombpnet_no_bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
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fold_2/logs.models.fold_2.ENCSR108SYM/logfile.modelling.fold_2.ENCSR108SYM.epoch_loss.csv ADDED
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