diff --git "a/train_job_output.txt" "b/train_job_output.txt"
--- "a/train_job_output.txt"
+++ "b/train_job_output.txt"
@@ -1,4 +1,4 @@
-slurm submission log: 2024-05-09 15:03:33.199064
+slurm submission log: 2024-05-10 08:21:53.371659
 created following sbatch script: 
 
 ###############################
@@ -8,22 +8,22 @@ created following sbatch script:
 #SBATCH --account=nlp
 #SBATCH --cpus-per-task=16
 #SBATCH --gres=gpu:2
-#SBATCH --job-name=tthrush-job-3941143
+#SBATCH --job-name=tthrush-job-2404107
 #SBATCH --mem=400G
-#SBATCH --nodelist=sphinx2
+#SBATCH --nodelist=sphinx1
 #SBATCH --open-mode=append
-#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_2/pythia-70m_sciq/train_job_output.txt
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq/train_job_output.txt
 #SBATCH --partition=sphinx
 #SBATCH --time=14-0
 
 # activate your desired anaconda environment
-. /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/etc/profile.d/conda.sh ; conda activate pretraining-coreset-selection
+. /nlp/scr/tthrush/miniconda3/etc/profile.d/conda.sh ; conda activate pretraining-coreset-selection
 
 # cd to working directory
 cd .
 
 # launch commands
-srun --unbuffered run_as_child_processes 'torchrun --master_port 29502 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_2/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_2/pythia-70m_sciq --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --num_train_epochs 14 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2'
+srun --unbuffered run_as_child_processes 'torchrun --master_port 29502 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_3/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --num_train_epochs 1 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2'
 
 ###############################
 
@@ -33,485 +33,105 @@ submission to slurm complete!
 ###############################
 slurm submission output
 
-Submitted batch job 7592321
+Submitted batch job 7593609
 
 
 
 ###############################
 
-/var/lib/slurm/slurmd/job7592321/slurm_script: line 15: /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/etc/profile.d/conda.sh: No such file or directory
+slurm submission log: 2024-05-10 08:23:19.470596
+created following sbatch script: 
 
-CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
-To initialize your shell, run
+###############################
 
-    $ conda init <SHELL_NAME>
+#!/bin/bash
 
-Currently supported shells are:
-  - bash
-  - fish
-  - tcsh
-  - xonsh
-  - zsh
-  - powershell
+#SBATCH --account=nlp
+#SBATCH --cpus-per-task=16
+#SBATCH --gres=gpu:2
+#SBATCH --job-name=tthrush-job-3619453
+#SBATCH --mem=400G
+#SBATCH --nodelist=sphinx2
+#SBATCH --open-mode=append
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq/train_job_output.txt
+#SBATCH --partition=sphinx
+#SBATCH --time=14-0
 
-See 'conda init --help' for more information and options.
+# activate your desired anaconda environment
+. /nlp/scr/tthrush/miniconda3/etc/profile.d/conda.sh ; conda activate pretraining-coreset-selection
 
-IMPORTANT: You may need to close and restart your shell after running 'conda init'.
+# cd to working directory
+cd .
 
+# launch commands
+srun --unbuffered run_as_child_processes 'torchrun --master_port 29502 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_3/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --num_train_epochs 1 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2'
+
+###############################
+
+submission to slurm complete!
+
+
+###############################
+slurm submission output
+
+Submitted batch job 7593622
+
+
+
+###############################
 
 ###############################
-start time: 2024-05-09 16:40:46.819377
+start time: 2024-05-10 15:02:42.471821
 machine: sphinx2
 conda env: pretraining-coreset-selection
 ###############################
 running following processes
 
-	torchrun --master_port 29502 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_2/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_2/pythia-70m_sciq --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --num_train_epochs 14 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2
+	torchrun --master_port 29502 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_3/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --num_train_epochs 1 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2
 
 
 ###############################
 command outputs: 
 
 
-[2024-05-09 16:40:54,330] torch.distributed.run: [WARNING] 
-[2024-05-09 16:40:54,330] torch.distributed.run: [WARNING] *****************************************
-[2024-05-09 16:40:54,330] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
-[2024-05-09 16:40:54,330] torch.distributed.run: [WARNING] *****************************************
-05/09/2024 16:40:58 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_2/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_2/pythia-70m_sciq', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=14, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)
-05/09/2024 16:40:58 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_2/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_2/pythia-70m_sciq', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=14, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)
-
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-[rank0]:[W reducer.cpp:1360] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration,  which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
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{'loss': 10.6537, 'grad_norm': 1.41543710231781, 'learning_rate': 2.3386342376052384e-05, 'epoch': 0.03}
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{'loss': 9.9361, 'grad_norm': 1.3332717418670654, 'learning_rate': 4.677268475210477e-05, 'epoch': 0.07}
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{'loss': 9.2222, 'grad_norm': 1.162742018699646, 'learning_rate': 7.015902712815715e-05, 'epoch': 0.1}
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{'loss': 8.4379, 'grad_norm': 0.8147327899932861, 'learning_rate': 9.354536950420954e-05, 'epoch': 0.13}
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                                                     {'loss': 7.784, 'grad_norm': 0.4891585409641266, 'learning_rate': 0.00011693171188026193, 'epoch': 0.16}
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                                                     {'loss': 6.593, 'grad_norm': 0.6057019233703613, 'learning_rate': 0.00018709073900841907, 'epoch': 0.26}
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                                                     {'loss': 6.1214, 'grad_norm': 0.848291277885437, 'learning_rate': 0.00023386342376052386, 'epoch': 0.33}
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{'loss': 5.4639, 'grad_norm': 0.7402798533439636, 'learning_rate': 0.0003507951356407858, 'epoch': 0.49}
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                                                     {'loss': 5.0668, 'grad_norm': 0.6643111705780029, 'learning_rate': 0.0004677268475210477, 'epoch': 0.65}
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                                                     {'loss': 4.9989, 'grad_norm': 0.5118005275726318, 'learning_rate': 0.0004911131898971, 'epoch': 0.69}
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{'loss': 4.8392, 'grad_norm': 0.5483365654945374, 'learning_rate': 0.0005612722170252572, 'epoch': 0.79}
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                                                     {'loss': 4.7939, 'grad_norm': 0.7277975082397461, 'learning_rate': 0.0005846585594013096, 'epoch': 0.82}
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                                                     {'loss': 4.7435, 'grad_norm': 0.5552908778190613, 'learning_rate': 0.0006080449017773621, 'epoch': 0.85}
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{'loss': 4.5319, 'grad_norm': 0.4785366952419281, 'learning_rate': 0.0007249766136576241, 'epoch': 1.02}
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                                                     {'loss': 4.4826, 'grad_norm': 0.44824910163879395, 'learning_rate': 0.0007483629560336763, 'epoch': 1.05}
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{'loss': 4.4396, 'grad_norm': 0.45654717087745667, 'learning_rate': 0.0007951356407857812, 'epoch': 1.11}
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                                                     {'loss': 4.3703, 'grad_norm': 0.3948267102241516, 'learning_rate': 0.0008652946679139383, 'epoch': 1.21}
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                                                     {'loss': 4.321, 'grad_norm': 0.403964638710022, 'learning_rate': 0.000912067352666043, 'epoch': 1.28}
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{'loss': 4.3076, 'grad_norm': 0.37247371673583984, 'learning_rate': 0.0009354536950420954, 'epoch': 1.31}
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{'loss': 4.2765, 'grad_norm': 0.36226823925971985, 'learning_rate': 0.0009588400374181479, 'epoch': 1.34}
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                                                      {'loss': 4.2573, 'grad_norm': 0.3463389575481415, 'learning_rate': 0.0009822263797942, 'epoch': 1.38}
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                                                      {'loss': 4.2325, 'grad_norm': 0.4508088231086731, 'learning_rate': 0.0009999990387768293, 'epoch': 1.41}
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{'loss': 4.2129, 'grad_norm': 0.322310209274292, 'learning_rate': 0.0009999743408927195, 'epoch': 1.44}
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{'loss': 4.1637, 'grad_norm': 0.3099164366722107, 'learning_rate': 0.0009998248272504882, 'epoch': 1.51}
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                                                      {'loss': 4.1434, 'grad_norm': 0.3336896002292633, 'learning_rate': 0.0009997000214725905, 'epoch': 1.54}
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{'loss': 4.1279, 'grad_norm': 0.327374130487442, 'learning_rate': 0.000999541860089067, 'epoch': 1.57}
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                                                      {'loss': 4.1024, 'grad_norm': 0.31598860025405884, 'learning_rate': 0.0009993503536573894, 'epoch': 1.6}
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                                                      {'loss': 4.0818, 'grad_norm': 0.30035948753356934, 'learning_rate': 0.0009991255149608528, 'epoch': 1.64}
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                                                      {'loss': 4.0706, 'grad_norm': 0.3048439919948578, 'learning_rate': 0.0009988673590077238, 'epoch': 1.67}
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{'loss': 4.0457, 'grad_norm': 0.31846246123313904, 'learning_rate': 0.0009985759030302366, 'epoch': 1.7}
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                                                      {'loss': 4.0303, 'grad_norm': 0.3052782714366913, 'learning_rate': 0.0009982511664834452, 'epoch': 1.74}
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{'loss': 4.0216, 'grad_norm': 0.297064870595932, 'learning_rate': 0.0009978931710439229, 'epoch': 1.77}
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{'loss': 4.0011, 'grad_norm': 0.2778494358062744, 'learning_rate': 0.000997501940608316, 'epoch': 1.8}
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                                                      {'loss': 3.9904, 'grad_norm': 0.2933351695537567, 'learning_rate': 0.0009970775012917489, 'epoch': 1.83}
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                                                      {'loss': 3.9772, 'grad_norm': 0.3018167018890381, 'learning_rate': 0.00099661988142608, 'epoch': 1.87}
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{'loss': 3.9578, 'grad_norm': 0.2643064558506012, 'learning_rate': 0.0009961291115580116, 'epoch': 1.9}
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                                                      {'loss': 3.9483, 'grad_norm': 0.2801077961921692, 'learning_rate': 0.0009956052244470509, 'epoch': 1.93}
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{'loss': 3.9345, 'grad_norm': 0.2734622061252594, 'learning_rate': 0.0009950482550633215, 'epoch': 1.96}
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                                                      {'loss': 3.9362, 'grad_norm': 0.278024286031723, 'learning_rate': 0.0009944582405852314, 'epoch': 2.0}
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{'loss': 3.7967, 'grad_norm': 0.2810928523540497, 'learning_rate': 0.0009931792360859792, 'epoch': 2.06}
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                                                      {'loss': 3.7937, 'grad_norm': 0.2628416121006012, 'learning_rate': 0.0009924903314399776, 'epoch': 2.1}
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                                                      {'loss': 3.7775, 'grad_norm': 0.2687695324420929, 'learning_rate': 0.0009917685524442382, 'epoch': 2.13}
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                                                      {'loss': 3.7873, 'grad_norm': 0.2711257338523865, 'learning_rate': 0.0009910139472784174, 'epoch': 2.16}
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{'loss': 3.7886, 'grad_norm': 0.26044875383377075, 'learning_rate': 0.0009902265663133602, 'epoch': 2.19}
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{'loss': 3.7833, 'grad_norm': 0.296349436044693, 'learning_rate': 0.0009894064621077375, 'epoch': 2.23}
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                                                      {'loss': 3.7739, 'grad_norm': 0.2820855677127838, 'learning_rate': 0.0009885536894045377, 'epoch': 2.26}
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                                                      {'loss': 3.7828, 'grad_norm': 0.25668656826019287, 'learning_rate': 0.0009876683051274124, 'epoch': 2.29}
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                                                      {'loss': 3.7616, 'grad_norm': 0.26414433121681213, 'learning_rate': 0.0009867503683768772, 'epoch': 2.32}
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                                                      {'loss': 3.7676, 'grad_norm': 0.26537370681762695, 'learning_rate': 0.0009857999404263656, 'epoch': 2.36}
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 17%|█▋        | 1825/10682 [15:38<1:12:47,  2.03it/s]{'loss': 3.7483, 'grad_norm': 0.2584211826324463, 'learning_rate': 0.0009848170847181403, 'epoch': 2.39}
                                                      
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{'loss': 3.7511, 'grad_norm': 0.2572576105594635, 'learning_rate': 0.0009838018668590573, 'epoch': 2.42}
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{'loss': 3.7482, 'grad_norm': 0.2456352263689041, 'learning_rate': 0.000982754354616187, 'epoch': 2.46}
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                                                      {'loss': 3.7398, 'grad_norm': 0.2749660909175873, 'learning_rate': 0.0009816746179122904, 'epoch': 2.49}
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{'loss': 3.7401, 'grad_norm': 0.26088210940361023, 'learning_rate': 0.0009805627288211524, 'epoch': 2.52}
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                                                      {'loss': 3.7259, 'grad_norm': 0.2577754557132721, 'learning_rate': 0.0009794187615627694, 'epoch': 2.55}
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                                                      {'loss': 3.716, 'grad_norm': 0.2473675161600113, 'learning_rate': 0.00097703490012545, 'epoch': 2.62}
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                                                      {'loss': 3.7081, 'grad_norm': 0.27898550033569336, 'learning_rate': 0.0009745236700927205, 'epoch': 2.69}
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                                                      {'loss': 3.7086, 'grad_norm': 0.2514036297798157, 'learning_rate': 0.000971885741964458, 'epoch': 2.75}
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                                                      {'loss': 3.7038, 'grad_norm': 0.2366958111524582, 'learning_rate': 0.0009691218200690053, 'epoch': 2.82}
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{'loss': 3.6922, 'grad_norm': 0.24879983067512512, 'learning_rate': 0.0009676928407650656, 'epoch': 2.85}
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                                                      {'loss': 3.6809, 'grad_norm': 0.24702751636505127, 'learning_rate': 0.0009662326423751136, 'epoch': 2.88}
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                                                      {'loss': 3.6845, 'grad_norm': 0.24947431683540344, 'learning_rate': 0.000964741322369231, 'epoch': 2.91}
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{'loss': 3.6715, 'grad_norm': 0.23864251375198364, 'learning_rate': 0.0009632189802949055, 'epoch': 2.95}
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                                                      {'loss': 3.6746, 'grad_norm': 0.2611524760723114, 'learning_rate': 0.0009616657177703876, 'epoch': 2.98}
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{'loss': 3.607, 'grad_norm': 0.2569226622581482, 'learning_rate': 0.0009600816384779067, 'epoch': 3.01}
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{'loss': 3.5097, 'grad_norm': 0.2544165849685669, 'learning_rate': 0.0009568214545962046, 'epoch': 3.08}
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                                                      {'loss': 3.5209, 'grad_norm': 0.27375468611717224, 'learning_rate': 0.0009551455676283627, 'epoch': 3.11}
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                                                      {'loss': 3.529, 'grad_norm': 0.2763053774833679, 'learning_rate': 0.0009499360750891371, 'epoch': 3.21}
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                                                      {'loss': 3.5334, 'grad_norm': 0.25160112977027893, 'learning_rate': 0.0009463127178640994, 'epoch': 3.27}
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                                                      {'loss': 3.5293, 'grad_norm': 0.24795430898666382, 'learning_rate': 0.0009425701948841596, 'epoch': 3.34}
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                                                      {'loss': 3.5328, 'grad_norm': 0.24955682456493378, 'learning_rate': 0.0009406545572679153, 'epoch': 3.37}
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                                                      {'loss': 3.5343, 'grad_norm': 0.24068914353847504, 'learning_rate': 0.0009387095054051274, 'epoch': 3.41}
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{'loss': 3.5204, 'grad_norm': 0.2708074450492859, 'learning_rate': 0.0009367351691304569, 'epoch': 3.44}
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{'loss': 3.541, 'grad_norm': 0.23952728509902954, 'learning_rate': 0.0009326991724491712, 'epoch': 3.5}
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                                                      {'loss': 3.5351, 'grad_norm': 0.25240790843963623, 'learning_rate': 0.0009306377814504165, 'epoch': 3.54}
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                                                      {'loss': 3.531, 'grad_norm': 0.24597875773906708, 'learning_rate': 0.0009285476448375166, 'epoch': 3.57}
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                                                      {'loss': 3.5247, 'grad_norm': 0.24853423237800598, 'learning_rate': 0.0009264289021297221, 'epoch': 3.6}
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                                                      {'loss': 3.5254, 'grad_norm': 0.23957444727420807, 'learning_rate': 0.0009221061660444758, 'epoch': 3.67}
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                                                      {'loss': 3.5236, 'grad_norm': 0.24744686484336853, 'learning_rate': 0.0009176707273677235, 'epoch': 3.73}
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{'loss': 3.5059, 'grad_norm': 0.2570688724517822, 'learning_rate': 0.0009012765247103541, 'epoch': 3.96}
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{'loss': 3.354, 'grad_norm': 0.24168278276920319, 'learning_rate': 0.0008963490065844889, 'epoch': 4.03}
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                                                      {'loss': 3.3471, 'grad_norm': 0.25673556327819824, 'learning_rate': 0.0008938454796549082, 'epoch': 4.06}
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{'loss': 3.354, 'grad_norm': 0.2632090449333191, 'learning_rate': 0.0008887597256191701, 'epoch': 4.13}
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                                                      {'loss': 3.3768, 'grad_norm': 0.2505457401275635, 'learning_rate': 0.000883570172510888, 'epoch': 4.19}
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                                                      {'loss': 3.3727, 'grad_norm': 0.24461257457733154, 'learning_rate': 0.0008809369032362939, 'epoch': 4.22}
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                                                      {'loss': 3.3786, 'grad_norm': 0.25147712230682373, 'learning_rate': 0.0008782782059437559, 'epoch': 4.26}
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                                                      {'loss': 3.3833, 'grad_norm': 0.25828418135643005, 'learning_rate': 0.0008755942581046657, 'epoch': 4.29}
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                                                      {'loss': 3.3885, 'grad_norm': 0.23787076771259308, 'learning_rate': 0.0008673927112327234, 'epoch': 4.39}
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                                                      {'loss': 3.38, 'grad_norm': 0.25981152057647705, 'learning_rate': 0.000864609569451406, 'epoch': 4.42}
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                                                    {'loss': 3.3867, 'grad_norm': 0.2358919382095337, 'learning_rate': 0.0008618020895222331, 'epoch': 4.45}
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                                                    {'loss': 3.3844, 'grad_norm': 0.24663330614566803, 'learning_rate': 0.0008589704588480251, 'epoch': 4.49}
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{'loss': 3.3931, 'grad_norm': 0.24412831664085388, 'learning_rate': 0.0008561148664436948, 'epoch': 4.52}
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                                                    {'loss': 3.3853, 'grad_norm': 0.25801965594291687, 'learning_rate': 0.0008503325604889736, 'epoch': 4.58}
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                                                    {'loss': 3.3977, 'grad_norm': 0.23720820248126984, 'learning_rate': 0.000841484205239968, 'epoch': 4.68}
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                                                    {'loss': 3.3826, 'grad_norm': 0.24208204448223114, 'learning_rate': 0.0008384889004421422, 'epoch': 4.72}
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{'loss': 3.3845, 'grad_norm': 0.23758889734745026, 'learning_rate': 0.0008354710010840066, 'epoch': 4.75}
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                                                    {'loss': 3.38, 'grad_norm': 0.2481546401977539, 'learning_rate': 0.0008324307086141438, 'epoch': 4.78}
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{'loss': 3.3883, 'grad_norm': 0.23900750279426575, 'learning_rate': 0.0008262837575938593, 'epoch': 4.85}
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                                                    {'loss': 3.3901, 'grad_norm': 0.275252103805542, 'learning_rate': 0.0008231775093601584, 'epoch': 4.88}
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{'loss': 3.2055, 'grad_norm': 0.2501608431339264, 'learning_rate': 0.0008073268776325152, 'epoch': 5.04}
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-05/09/2024 17:13:59 - WARNING - huggingface_hub.utils._http - HTTP Error 500 thrown while requesting PUT https://hf-hub-lfs-us-east-1.s3-accelerate.amazonaws.com/repos/65/59/6559f9fd0fe510b6e2f18c5c8386304be1c7636b3e22d492f188f53ed07d4c4f/39e4e41aac9aec1971396046318ffde01d1fedeb82ab321761b9a17c8bb46e04?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQFN2FTF47%2F20240510%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240510T001346Z&X-Amz-Expires=86400&X-Amz-Signature=0ea7535bff59898bba007f0edb12af88f55c3cff671677261f9a8b6783252a10&X-Amz-SignedHeaders=host&partNumber=2&uploadId=bGL0C2pWLjx2rnDOwBrpFYc9IKtlErBOHIWRyZArUrGlzsvXBdhXis7cfLMF7o_aUMOOaywny.B4yy9r_JZfWBwA_2j9YQ.pWbUwK1kxJ04jGn8QYc2IbebLqQtZyDDm&x-id=UploadPart
-05/09/2024 17:13:59 - WARNING - huggingface_hub.utils._http - Retrying in 1s [Retry 1/5].
-Retrying in 1s [Retry 1/5].
-
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{'loss': 3.2496, 'grad_norm': 0.25571322441101074, 'learning_rate': 0.00079096345296872, 'epoch': 5.21}
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{'loss': 3.2663, 'grad_norm': 0.24902372062206268, 'learning_rate': 0.0007842805893115124, 'epoch': 5.27}
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                                                    {'loss': 3.2625, 'grad_norm': 0.25352743268013, 'learning_rate': 0.0007809105815091867, 'epoch': 5.3}
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{'loss': 3.2588, 'grad_norm': 0.2440648078918457, 'learning_rate': 0.0007775218225718394, 'epoch': 5.34}
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                                                    {'loss': 3.2518, 'grad_norm': 0.2516688406467438, 'learning_rate': 0.0007706889573443467, 'epoch': 5.4}
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                                                    {'loss': 3.2696, 'grad_norm': 0.28046825528144836, 'learning_rate': 0.0007672453071565586, 'epoch': 5.44}
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                                                    {'loss': 3.2692, 'grad_norm': 0.24219585955142975, 'learning_rate': 0.0007603047209574854, 'epoch': 5.5}
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{'loss': 3.2713, 'grad_norm': 0.28504911065101624, 'learning_rate': 0.0007532946332467235, 'epoch': 5.57}
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{'loss': 3.273, 'grad_norm': 0.24615144729614258, 'learning_rate': 0.0007497641105186759, 'epoch': 5.6}
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{'loss': 3.2894, 'grad_norm': 0.23486711084842682, 'learning_rate': 0.0007462169157217631, 'epoch': 5.63}
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                                                    {'loss': 3.2814, 'grad_norm': 0.25793495774269104, 'learning_rate': 0.0007426532856357045, 'epoch': 5.66}
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{'loss': 3.2855, 'grad_norm': 0.2468792051076889, 'learning_rate': 0.0007354776721845277, 'epoch': 5.73}
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{'loss': 3.2721, 'grad_norm': 0.258327454328537, 'learning_rate': 0.0007172678028031901, 'epoch': 5.89}
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                                                    {'loss': 3.283, 'grad_norm': 0.24208632111549377, 'learning_rate': 0.0007098806259143232, 'epoch': 5.96}
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                                                    {'loss': 3.1444, 'grad_norm': 0.27156001329421997, 'learning_rate': 0.0007024374107764318, 'epoch': 6.02}
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{'loss': 3.1578, 'grad_norm': 0.29045844078063965, 'learning_rate': 0.000679791480919905, 'epoch': 6.22}
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{'loss': 3.1482, 'grad_norm': 0.25838011503219604, 'learning_rate': 0.000675973677619089, 'epoch': 6.25}
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{'loss': 3.1557, 'grad_norm': 0.24932105839252472, 'learning_rate': 0.0006721441278537161, 'epoch': 6.29}
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                                                    {'loss': 3.1702, 'grad_norm': 0.2541992664337158, 'learning_rate': 0.0006644508122054031, 'epoch': 6.35}
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                                                    {'loss': 3.1654, 'grad_norm': 0.2546573579311371, 'learning_rate': 0.0006605875598609699, 'epoch': 6.39}
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                                                    {'loss': 3.1751, 'grad_norm': 0.24312809109687805, 'learning_rate': 0.0006567135880947134, 'epoch': 6.42}
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{'loss': 3.18, 'grad_norm': 0.25348642468452454, 'learning_rate': 0.0006411156890315328, 'epoch': 6.55}
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{'loss': 3.1791, 'grad_norm': 0.25058817863464355, 'learning_rate': 0.0006371920127491398, 'epoch': 6.58}
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                                                    {'loss': 3.1692, 'grad_norm': 0.24779805541038513, 'learning_rate': 0.0006332591787271516, 'epoch': 6.61}
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                                                    {'loss': 3.18, 'grad_norm': 0.24813100695610046, 'learning_rate': 0.0006293174494871916, 'epoch': 6.65}
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{'loss': 3.1766, 'grad_norm': 0.2555025815963745, 'learning_rate': 0.0006214083583911186, 'epoch': 6.71}
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{'loss': 3.1836, 'grad_norm': 0.250825971364975, 'learning_rate': 0.0006134668511928376, 'epoch': 6.78}
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{'loss': 3.1864, 'grad_norm': 0.259960412979126, 'learning_rate': 0.0006014984507777682, 'epoch': 6.88}
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{'loss': 3.1968, 'grad_norm': 0.24892860651016235, 'learning_rate': 0.000593485197556533, 'epoch': 6.94}
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                                                    {'loss': 3.0187, 'grad_norm': 0.2564186453819275, 'learning_rate': 0.0005814191870410933, 'epoch': 7.04}
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{'loss': 3.0352, 'grad_norm': 0.26490676403045654, 'learning_rate': 0.0005733475583803009, 'epoch': 7.11}
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                                                    {'loss': 3.0387, 'grad_norm': 0.2609146535396576, 'learning_rate': 0.0005693042652030427, 'epoch': 7.14}
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{'loss': 3.0447, 'grad_norm': 0.25717926025390625, 'learning_rate': 0.0005652563458788184, 'epoch': 7.17}
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{'loss': 3.0555, 'grad_norm': 0.26100456714630127, 'learning_rate': 0.0005612040706113396, 'epoch': 7.2}
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{'loss': 3.0649, 'grad_norm': 0.25406453013420105, 'learning_rate': 0.0005571477098950832, 'epoch': 7.24}
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{'loss': 3.0685, 'grad_norm': 0.27719518542289734, 'learning_rate': 0.0005490238154396129, 'epoch': 7.3}
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{'loss': 3.0732, 'grad_norm': 0.2697433531284332, 'learning_rate': 0.0005368141099658168, 'epoch': 7.4}
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{'loss': 3.0911, 'grad_norm': 0.2737847864627838, 'learning_rate': 0.0005286615665623071, 'epoch': 7.47}
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{'loss': 3.0746, 'grad_norm': 0.2656842768192291, 'learning_rate': 0.0005205013705038776, 'epoch': 7.53}
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                                                    {'loss': 3.0821, 'grad_norm': 0.2617127597332001, 'learning_rate': 0.0005164190835329964, 'epoch': 7.56}
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{'loss': 3.0771, 'grad_norm': 0.2714592516422272, 'learning_rate': 0.0005123357005676156, 'epoch': 7.6}
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                                                    {'loss': 3.1041, 'grad_norm': 0.2582048177719116, 'learning_rate': 0.0005082514941786895, 'epoch': 7.63}
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                                                    {'loss': 3.0928, 'grad_norm': 0.25759726762771606, 'learning_rate': 0.0005041667369921374, 'epoch': 7.66}
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                                                    {'loss': 3.0921, 'grad_norm': 0.2588006258010864, 'learning_rate': 0.0004959966608954618, 'epoch': 7.73}
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                                                    {'loss': 3.1064, 'grad_norm': 0.26175829768180847, 'learning_rate': 0.00047966189651337725, 'epoch': 7.86}
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                                                    {'loss': 3.0987, 'grad_norm': 0.2673705220222473, 'learning_rate': 0.0004674241234809751, 'epoch': 7.96}
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                                                    {'loss': 3.1022, 'grad_norm': 0.253995418548584, 'learning_rate': 0.0004633488518231793, 'epoch': 7.99}
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{'loss': 2.9833, 'grad_norm': 0.2493210732936859, 'learning_rate': 0.00045927602667567333, 'epoch': 8.02}
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                                                    {'loss': 2.9362, 'grad_norm': 0.2625344395637512, 'learning_rate': 0.00045520591990466365, 'epoch': 8.06}
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                                                    {'loss': 2.9675, 'grad_norm': 0.2638459801673889, 'learning_rate': 0.00044301462568205915, 'epoch': 8.15}
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                                                    {'loss': 2.9643, 'grad_norm': 0.2715643346309662, 'learning_rate': 0.0004389581071780553, 'epoch': 8.19}
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                                                    {'loss': 2.979, 'grad_norm': 0.26490533351898193, 'learning_rate': 0.0004349056632972576, 'epoch': 8.22}
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                                                    {'loss': 2.9921, 'grad_norm': 0.2598678171634674, 'learning_rate': 0.0004268140811381641, 'epoch': 8.28}
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                                                    {'loss': 2.993, 'grad_norm': 0.2814801037311554, 'learning_rate': 0.00041471402041183287, 'epoch': 8.38}
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{'loss': 2.9936, 'grad_norm': 0.2589092552661896, 'learning_rate': 0.0003906748398221429, 'epoch': 8.58}
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                                                    {'loss': 3.0135, 'grad_norm': 0.2620540261268616, 'learning_rate': 0.00038271731370291583, 'epoch': 8.64}
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{'loss': 3.0054, 'grad_norm': 0.2683119773864746, 'learning_rate': 0.00036296512652851323, 'epoch': 8.81}
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{'loss': 2.9963, 'grad_norm': 0.2591618299484253, 'learning_rate': 0.00035904107890373196, 'epoch': 8.84}
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{'loss': 3.0206, 'grad_norm': 0.2635193169116974, 'learning_rate': 0.00034732643572487243, 'epoch': 8.94}
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                                                    {'loss': 3.0199, 'grad_norm': 0.2645472586154938, 'learning_rate': 0.000343441590084772, 'epoch': 8.97}
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{'loss': 2.9851, 'grad_norm': 0.2988123893737793, 'learning_rate': 0.0003395671949156626, 'epoch': 9.0}
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                                                    {'loss': 2.8819, 'grad_norm': 0.26469868421554565, 'learning_rate': 0.0003280092948503962, 'epoch': 9.1}
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                                                    {'loss': 2.883, 'grad_norm': 0.2707022428512573, 'learning_rate': 0.00032417928053832723, 'epoch': 9.14}
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                                                    {'loss': 2.879, 'grad_norm': 0.26636505126953125, 'learning_rate': 0.0003203610024806651, 'epoch': 9.17}
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{'loss': 2.889, 'grad_norm': 0.2684054970741272, 'learning_rate': 0.0003165547155522783, 'epoch': 9.2}
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                                                      {'loss': 2.8916, 'grad_norm': 0.2807353138923645, 'learning_rate': 0.0003127606738276115, 'epoch': 9.23}
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                                                      {'loss': 2.8971, 'grad_norm': 0.26620224118232727, 'learning_rate': 0.00030897913056372755, 'epoch': 9.27}
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                                                      {'loss': 2.8974, 'grad_norm': 0.27408939599990845, 'learning_rate': 0.00030521033818340054, 'epoch': 9.3}
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{'loss': 2.9172, 'grad_norm': 0.2685629725456238, 'learning_rate': 0.0002977120114920343, 'epoch': 9.36}
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                                                      {'loss': 2.9093, 'grad_norm': 0.27699965238571167, 'learning_rate': 0.00029398297770374336, 'epoch': 9.4}
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{'loss': 2.9294, 'grad_norm': 0.2778185307979584, 'learning_rate': 0.0002865664138138335, 'epoch': 9.46}
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{'loss': 2.9175, 'grad_norm': 0.26997700333595276, 'learning_rate': 0.0002828793787771929, 'epoch': 9.5}
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{'loss': 2.9256, 'grad_norm': 0.27365386486053467, 'learning_rate': 0.0002792068368154043, 'epoch': 9.53}
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                                                      {'loss': 2.9307, 'grad_norm': 0.2683810591697693, 'learning_rate': 0.00026827861591187944, 'epoch': 9.63}
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{'loss': 2.9338, 'grad_norm': 0.26419082283973694, 'learning_rate': 0.00026466648779812794, 'epoch': 9.66}
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{'loss': 2.9327, 'grad_norm': 0.2663451135158539, 'learning_rate': 0.0002610700684926339, 'epoch': 9.69}
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{'loss': 2.9208, 'grad_norm': 0.2662382423877716, 'learning_rate': 0.00025392531550387867, 'epoch': 9.76}
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{'loss': 2.933, 'grad_norm': 0.2700079083442688, 'learning_rate': 0.0002503774587418758, 'epoch': 9.79}
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                                                      {'loss': 2.9204, 'grad_norm': 0.2628709673881531, 'learning_rate': 0.00024333196878634163, 'epoch': 9.86}
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{'loss': 2.9279, 'grad_norm': 0.26213338971138, 'learning_rate': 0.00023983480588813622, 'epoch': 9.89}
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                                                      {'loss': 2.9543, 'grad_norm': 0.27111098170280457, 'learning_rate': 0.00023635500934422239, 'epoch': 9.92}
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{'loss': 2.9468, 'grad_norm': 0.27557408809661865, 'learning_rate': 0.00023289281143540065, 'epoch': 9.95}
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{'loss': 2.8611, 'grad_norm': 0.281035840511322, 'learning_rate': 0.00022602213475715589, 'epoch': 10.02}
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{'loss': 2.8005, 'grad_norm': 0.27186882495880127, 'learning_rate': 0.0002226141146140523, 'epoch': 10.05}
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{'loss': 2.8169, 'grad_norm': 0.2712630331516266, 'learning_rate': 0.00021922461032806601, 'epoch': 10.09}
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{'loss': 2.8163, 'grad_norm': 0.27432700991630554, 'learning_rate': 0.0002158538481528759, 'epoch': 10.12}
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{'loss': 2.8211, 'grad_norm': 0.2715729773044586, 'learning_rate': 0.00020916944887928359, 'epoch': 10.18}
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{'loss': 2.8289, 'grad_norm': 0.2772938907146454, 'learning_rate': 0.00020585625797294927, 'epoch': 10.22}
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{'loss': 2.8212, 'grad_norm': 0.2719649076461792, 'learning_rate': 0.00020256270153176371, 'epoch': 10.25}
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{'loss': 2.8414, 'grad_norm': 0.27529338002204895, 'learning_rate': 0.00019603537011569566, 'epoch': 10.31}
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{'loss': 2.8396, 'grad_norm': 0.2769433259963989, 'learning_rate': 0.0001863970843282357, 'epoch': 10.41}
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{'loss': 2.852, 'grad_norm': 0.27252912521362305, 'learning_rate': 0.00017075473199874692, 'epoch': 10.58}
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                                                      {'loss': 2.8546, 'grad_norm': 0.2722909450531006, 'learning_rate': 0.00016769136599599017, 'epoch': 10.61}
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{'loss': 2.8525, 'grad_norm': 0.27568942308425903, 'learning_rate': 0.00015863517062339038, 'epoch': 10.71}
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{'loss': 2.8585, 'grad_norm': 0.27291959524154663, 'learning_rate': 0.00015566174472640188, 'epoch': 10.74}
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{'loss': 2.8559, 'grad_norm': 0.27311572432518005, 'learning_rate': 0.0001527113038415231, 'epoch': 10.77}
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                                                      {'loss': 2.8571, 'grad_norm': 0.2763269543647766, 'learning_rate': 0.00014114330604645943, 'epoch': 10.9}
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{'loss': 2.8635, 'grad_norm': 0.2721956968307495, 'learning_rate': 0.00013831071326327282, 'epoch': 10.94}
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{'loss': 2.7557, 'grad_norm': 0.27638164162635803, 'learning_rate': 0.0001272236408261237, 'epoch': 11.07}
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                                                      {'loss': 2.7808, 'grad_norm': 0.2801077663898468, 'learning_rate': 0.0001165346678316832, 'epoch': 11.2}
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{'loss': 2.7783, 'grad_norm': 0.28348976373672485, 'learning_rate': 0.00011392597484393285, 'epoch': 11.23}
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{'loss': 2.7817, 'grad_norm': 0.28865718841552734, 'learning_rate': 0.00011134305278348312, 'epoch': 11.26}
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                                                      {'loss': 2.78, 'grad_norm': 0.2784369885921478, 'learning_rate': 0.00010878607406363367, 'epoch': 11.3}
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{'loss': 2.7789, 'grad_norm': 0.27582377195358276, 'learning_rate': 0.00010625520936593375, 'epoch': 11.33}
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{'loss': 2.7909, 'grad_norm': 0.28055277466773987, 'learning_rate': 8.928431747505355e-05, 'epoch': 11.56}
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{'loss': 2.7797, 'grad_norm': 0.27887654304504395, 'learning_rate': 8.6968297974584e-05, 'epoch': 11.59}
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{'loss': 2.7831, 'grad_norm': 0.2778463661670685, 'learning_rate': 7.798144214020909e-05, 'epoch': 11.72}
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{'loss': 2.8144, 'grad_norm': 0.27680227160453796, 'learning_rate': 7.365644059145782e-05, 'epoch': 11.79}
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{'loss': 2.8089, 'grad_norm': 0.27644211053848267, 'learning_rate': 7.153655656890773e-05, 'epoch': 11.82}
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                                                      {'loss': 2.7967, 'grad_norm': 0.2740754783153534, 'learning_rate': 6.94452730207023e-05, 'epoch': 11.85}
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{'loss': 2.7975, 'grad_norm': 0.27586477994918823, 'learning_rate': 6.1368906655978e-05, 'epoch': 11.98}
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{'loss': 2.7676, 'grad_norm': 0.27505698800086975, 'learning_rate': 5.94226809108499e-05, 'epoch': 12.02}
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{'loss': 2.7402, 'grad_norm': 0.2807002365589142, 'learning_rate': 5.3760968048319145e-05, 'epoch': 12.12}
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{'loss': 2.7361, 'grad_norm': 0.2769155502319336, 'learning_rate': 5.193313847098613e-05, 'epoch': 12.15}
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{'loss': 2.7438, 'grad_norm': 0.28487518429756165, 'learning_rate': 4.492210053786228e-05, 'epoch': 12.28}
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{'loss': 2.7506, 'grad_norm': 0.2781054675579071, 'learning_rate': 4.1598380727865315e-05, 'epoch': 12.34}
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                                                      {'loss': 2.7417, 'grad_norm': 0.2766771912574768, 'learning_rate': 3.998236419395806e-05, 'epoch': 12.38}
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{'loss': 2.743, 'grad_norm': 0.2769390642642975, 'learning_rate': 3.6842557216818006e-05, 'epoch': 12.44}
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{'loss': 2.7423, 'grad_norm': 0.2786850035190582, 'learning_rate': 3.531897635965431e-05, 'epoch': 12.48}
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{'loss': 2.7433, 'grad_norm': 0.27557793259620667, 'learning_rate': 3.382641354591731e-05, 'epoch': 12.51}
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{'loss': 2.7433, 'grad_norm': 0.27862924337387085, 'learning_rate': 3.2364968406054075e-05, 'epoch': 12.54}
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{'loss': 2.7532, 'grad_norm': 0.2782875597476959, 'learning_rate': 3.093473849336781e-05, 'epoch': 12.57}
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                                                      {'loss': 2.7574, 'grad_norm': 0.27770131826400757, 'learning_rate': 2.6832284358471516e-05, 'epoch': 12.67}
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                                                      {'loss': 2.749, 'grad_norm': 0.27603113651275635, 'learning_rate': 2.5527849119658387e-05, 'epoch': 12.7}
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                                                      {'loss': 2.756, 'grad_norm': 0.27851659059524536, 'learning_rate': 2.4255085494343522e-05, 'epoch': 12.74}
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                                                      {'loss': 2.7534, 'grad_norm': 0.2752934694290161, 'learning_rate': 2.301407844110154e-05, 'epoch': 12.77}
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                                                      {'loss': 2.7569, 'grad_norm': 0.27959272265434265, 'learning_rate': 2.1804910798715826e-05, 'epoch': 12.8}
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{'loss': 2.7449, 'grad_norm': 0.2788638174533844, 'learning_rate': 2.0627663280649135e-05, 'epoch': 12.84}
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{'loss': 2.7531, 'grad_norm': 0.276666522026062, 'learning_rate': 1.9482414469655486e-05, 'epoch': 12.87}
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{'loss': 2.7553, 'grad_norm': 0.27473241090774536, 'learning_rate': 1.7288216615031272e-05, 'epoch': 12.93}
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{'loss': 2.7502, 'grad_norm': 0.27606716752052307, 'learning_rate': 1.5222903086944684e-05, 'epoch': 13.0}
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{'loss': 2.7218, 'grad_norm': 0.27606499195098877, 'learning_rate': 1.4238751618640577e-05, 'epoch': 13.03}
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                                                       {'loss': 2.7229, 'grad_norm': 0.27850425243377686, 'learning_rate': 1.1481100210606388e-05, 'epoch': 13.13}
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{'loss': 2.7154, 'grad_norm': 0.278669148683548, 'learning_rate': 9.805609925895964e-06, 'epoch': 13.2}
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{'loss': 2.7198, 'grad_norm': 0.2754727602005005, 'learning_rate': 7.537908845868024e-06, 'epoch': 13.29}
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{'loss': 2.7194, 'grad_norm': 0.27826181054115295, 'learning_rate': 6.847688328344037e-06, 'epoch': 13.33}
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{'loss': 2.7272, 'grad_norm': 0.2759071886539459, 'learning_rate': 5.56604678228706e-06, 'epoch': 13.39}
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{'loss': 2.7285, 'grad_norm': 0.2825750410556793, 'learning_rate': 4.416419388921844e-06, 'epoch': 13.46}
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                                                       {'loss': 2.7085, 'grad_norm': 0.27976953983306885, 'learning_rate': 3.3991130994299734e-06, 'epoch': 13.52}
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                                                       {'loss': 2.7195, 'grad_norm': 0.27882423996925354, 'learning_rate': 2.940166632433183e-06, 'epoch': 13.56}
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                                                       {'loss': 2.718, 'grad_norm': 0.27269044518470764, 'learning_rate': 2.5143995351817882e-06, 'epoch': 13.59}
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{'loss': 2.7171, 'grad_norm': 0.27644971013069153, 'learning_rate': 1.4364475817401635e-06, 'epoch': 13.69}
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{'loss': 2.7396, 'grad_norm': 0.2743651270866394, 'learning_rate': 1.143659993153079e-06, 'epoch': 13.72}
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{'loss': 2.7214, 'grad_norm': 0.27342525124549866, 'learning_rate': 8.841716933915555e-07, 'epoch': 13.75}
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                                                       {'loss': 2.7211, 'grad_norm': 0.27586132287979126, 'learning_rate': 6.580000036264244e-07, 'epoch': 13.79}
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                                                       {'loss': 2.7213, 'grad_norm': 0.274465411901474, 'learning_rate': 4.651600211027507e-07, 'epoch': 13.82}
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{'loss': 2.7337, 'grad_norm': 0.27669960260391235, 'learning_rate': 3.0566461813213986e-07, 'epoch': 13.85}
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{'loss': 2.7176, 'grad_norm': 0.2742961347103119, 'learning_rate': 1.7952444123359167e-07, 'epoch': 13.88}
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{'loss': 2.7211, 'grad_norm': 0.27650344371795654, 'learning_rate': 8.674791042273533e-08, 'epoch': 13.92}
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{'loss': 2.7335, 'grad_norm': 0.2771333158016205, 'learning_rate': 2.7341218649834522e-08, 'epoch': 13.95}
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{'loss': 2.7235, 'grad_norm': 0.27846845984458923, 'learning_rate': 1.3083313863404555e-09, 'epoch': 13.98}
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                                                       {'train_runtime': 5458.5567, 'train_samples_per_second': 2004.004, 'train_steps_per_second': 1.957, 'train_loss': 3.3834208510069783, 'epoch': 13.99}
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+[2024-05-10 15:02:45,277] torch.distributed.run: [WARNING] 
+[2024-05-10 15:02:45,277] torch.distributed.run: [WARNING] *****************************************
+[2024-05-10 15:02:45,277] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+[2024-05-10 15:02:45,277] torch.distributed.run: [WARNING] *****************************************
+05/10/2024 15:02:52 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_3/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)
+05/10/2024 15:02:52 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_3/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_3/pythia-70m_sciq', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)
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+[rank1]:[W reducer.cpp:1360] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration,  which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
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                                                {'loss': 9.8343, 'grad_norm': 0.9369164705276489, 'learning_rate': 0.0003246753246753247, 'epoch': 0.03}
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                                                {'loss': 7.3748, 'grad_norm': 0.3545825183391571, 'learning_rate': 0.0006493506493506494, 'epoch': 0.07}
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{'loss': 5.8974, 'grad_norm': 0.5354925394058228, 'learning_rate': 0.000974025974025974, 'epoch': 0.1}
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                                                 {'loss': 4.6084, 'grad_norm': 0.2889716327190399, 'learning_rate': 0.0009879683689693263, 'epoch': 0.16}
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{'loss': 3.1922, 'grad_norm': 0.4128451645374298, 'learning_rate': 0.0008081514142000517, 'epoch': 0.36}
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                                                 {'loss': 3.0883, 'grad_norm': 0.3450576961040497, 'learning_rate': 0.0007611516571398591, 'epoch': 0.39}
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{'loss': 2.9938, 'grad_norm': 0.4092760384082794, 'learning_rate': 0.000710732500322581, 'epoch': 0.43}
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                                                 {'loss': 2.3795, 'grad_norm': 0.35245397686958313, 'learning_rate': 0.0001329553403026331, 'epoch': 0.79}
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{'loss': 2.3126, 'grad_norm': 0.33316919207572937, 'learning_rate': 7.552007469355249e-06, 'epoch': 0.95}
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{'train_runtime': 493.6697, 'train_samples_per_second': 1582.627, 'train_steps_per_second': 1.546, 'train_loss': 3.4241124799335925, 'epoch': 1.0}
+
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 Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.