deploy: 36a17ad

FAIR-Chem · Jul 10, 2024 · 780fe35 · 780fe35
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diff --git a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt
diff --git a/_downloads/819e10305ddd6839cd7da05935b17060/mass-inference.txt b/_downloads/819e10305ddd6839cd7da05935b17060/mass-inference.txt
@@ -1,16 +1,16 @@
-2024-07-09 14:17:18 (INFO): Running in non-distributed local mode
-2024-07-09 14:17:19 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem
-2024-07-09 14:17:20 (INFO): amp: true
+2024-07-10 16:34:01 (INFO): Running in non-distributed local mode
+2024-07-10 16:34:01 (INFO): Project root: /home/runner/work/fairchem/fairchem/src/fairchem
+2024-07-10 16:34:02 (INFO): amp: true
 cmd:
-  checkpoint_dir: ./checkpoints/2024-07-09-14-17-36
-  commit: bf2b26e
+  checkpoint_dir: ./checkpoints/2024-07-10-16-34-08
+  commit: 36a17ad
   identifier: ''
-  logs_dir: ./logs/tensorboard/2024-07-09-14-17-36
+  logs_dir: ./logs/tensorboard/2024-07-10-16-34-08
   print_every: 10
-  results_dir: ./results/2024-07-09-14-17-36
+  results_dir: ./results/2024-07-10-16-34-08
   seed: 0
-  timestamp_id: 2024-07-09-14-17-36
-  version: 0.1.dev1+gbf2b26e
+  timestamp_id: 2024-07-10-16-34-08
+  version: 0.1.dev1+g36a17ad
 dataset: null
 evaluation_metrics:
   metrics:
@@ -112,20 +112,20 @@ test_dataset:
 trainer: ocp
 val_dataset: null
 
-2024-07-09 14:17:20 (INFO): rank: 0: Sampler created...
-2024-07-09 14:17:20 (INFO): Batch balancing is disabled for single GPU training.
-2024-07-09 14:17:20 (INFO): Loading model: gemnet_t
-2024-07-09 14:17:22 (INFO): Loaded GemNetT with 31671825 parameters.
-2024-07-09 14:17:22 (WARNING): log_summary for Tensorboard not supported
-2024-07-09 14:17:22 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gndt_oc22_all_s2ef.pt
-2024-07-09 14:17:22 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. 
-2024-07-09 14:17:22 (WARNING): Scale factor comment not found in model
-2024-07-09 14:17:22 (INFO): Predicting on test.
+2024-07-10 16:34:02 (INFO): rank: 0: Sampler created...
+2024-07-10 16:34:02 (INFO): Batch balancing is disabled for single GPU training.
+2024-07-10 16:34:02 (INFO): Loading model: gemnet_t
+2024-07-10 16:34:04 (INFO): Loaded GemNetT with 31671825 parameters.
+2024-07-10 16:34:04 (WARNING): log_summary for Tensorboard not supported
+2024-07-10 16:34:04 (INFO): Loading checkpoint from: /tmp/ocp_checkpoints/gndt_oc22_all_s2ef.pt
+2024-07-10 16:34:04 (INFO): Overwriting scaling factors with those loaded from checkpoint. If you're generating predictions with a pretrained checkpoint, this is the correct behavior. To disable this, delete `scale_dict` from the checkpoint. 
+2024-07-10 16:34:04 (WARNING): Scale factor comment not found in model
+2024-07-10 16:34:04 (INFO): Predicting on test.
 device 0:   0%|                                           | 0/3 [00:00<?, ?it/s]/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
   storage = elem.storage()._new_shared(numel)
 /opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch_geometric/data/collate.py:145: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
   storage = elem.storage()._new_shared(numel)
-device 0:  33%|███████████▋                       | 1/3 [00:02<00:04,  2.03s/it]device 0:  67%|███████████████████████▎           | 2/3 [00:04<00:02,  2.51s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:06<00:00,  2.11s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:06<00:00,  2.18s/it]
-2024-07-09 14:17:28 (INFO): Writing results to ./results/2024-07-09-14-17-36/ocp_predictions.npz
-2024-07-09 14:17:28 (INFO): Total time taken: 6.688116550445557
-Elapsed time = 13.0 seconds
+device 0:  33%|███████████▋                       | 1/3 [00:03<00:07,  3.82s/it]device 0:  67%|███████████████████████▎           | 2/3 [00:07<00:03,  3.47s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:08<00:00,  2.43s/it]device 0: 100%|███████████████████████████████████| 3/3 [00:08<00:00,  2.76s/it]
+2024-07-10 16:34:13 (INFO): Writing results to ./results/2024-07-10-16-34-08/ocp_predictions.npz
+2024-07-10 16:34:13 (INFO): Total time taken: 8.430647373199463
+Elapsed time = 14.9 seconds

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diff --git a/core/fine-tuning/fine-tuning-oxides.html b/core/fine-tuning/fine-tuning-oxides.html
@@ -827,7 +827,7 @@ <h1>Fine tuning a model<a class="headerlink" href="#fine-tuning-a-model" title="
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Elapsed time 67.7 seconds.
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Elapsed time 68.0 seconds.
 </pre></div>
 </div>
 <img alt="../../_images/e09235df67f6a4f604e2dc396140b3979de3a415db6696093790df3189ca2edf.png" src="../../_images/e09235df67f6a4f604e2dc396140b3979de3a415db6696093790df3189ca2edf.png" />
@@ -906,7 +906,7 @@ <h1>Fine tuning the checkpoint<a class="headerlink" href="#fine-tuning-the-check
 </div>
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 <div class="cell_output docutils container">
-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_2423/1448814737.py:12: DeprecationWarning: Please use atoms.calc = calc
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_2290/1448814737.py:12: DeprecationWarning: Please use atoms.calc = calc
   atoms.set_calculator(calc)
 </pre></div>
 </div>
@@ -1199,7 +1199,7 @@ <h2>Running the training job<a class="headerlink" href="#running-the-training-jo
 <span class="expanded">Hide code cell output</span>
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Elapsed time = 206.6 seconds
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Elapsed time = 207.0 seconds
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@@ -1215,7 +1215,7 @@ <h2>Running the training job<a class="headerlink" href="#running-the-training-jo
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&#39;fine-tuning/checkpoints/2024-07-09-14-11-12-ft-oxides&#39;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&#39;fine-tuning/checkpoints/2024-07-10-16-27-44-ft-oxides&#39;
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@@ -1274,7 +1274,7 @@ <h2>Running the training job<a class="headerlink" href="#running-the-training-jo
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-<img alt="../../_images/ec3d78c828a48f27837aed2db2ea620c401fa3cc7fec032fead69ca09d84fb29.png" src="../../_images/ec3d78c828a48f27837aed2db2ea620c401fa3cc7fec032fead69ca09d84fb29.png" />
+<img alt="../../_images/5619bffc5cbf78888b670444701903eb7a06f1d9b467bceef578151bc4f956c6.png" src="../../_images/5619bffc5cbf78888b670444701903eb7a06f1d9b467bceef578151bc4f956c6.png" />
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>New MAE = 0.324 eV/atom
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>New MAE = 0.235 eV/atom
 </pre></div>
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@@ -1304,7 +1304,7 @@ <h2>Running the training job<a class="headerlink" href="#running-the-training-jo
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+<img alt="../../_images/336759a1dc6295bc0edbf0a0fb8b76b26c6259d18205582f40cff7f41c093c24.png" src="../../_images/336759a1dc6295bc0edbf0a0fb8b76b26c6259d18205582f40cff7f41c093c24.png" />
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 <p>It is possible to continue refining the fit. The simple things to do are to use more epochs of training. Eventually the MAE will stabilize, and then it may be necessary to adjust other optimization parameters like the learning rate (usually you decrease it).</p>