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: 2024-05-11 08:25:30.779602
+slurm submission log: 2024-05-11 17:54:08.580940
 created following sbatch script: 
 
 ###############################
@@ -7,13 +7,13 @@ created following sbatch script:
 
 #SBATCH --account=nlp
 #SBATCH --cpus-per-task=16
-#SBATCH --dependency=afterok:7597679
+#SBATCH --dependency=afterok:
 #SBATCH --gres=gpu:2
-#SBATCH --job-name=tthrush-job-3883841
+#SBATCH --job-name=tthrush-job-4732981
 #SBATCH --mem=400G
 #SBATCH --nodelist=sphinx2
 #SBATCH --open-mode=append
-#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_4/pythia-70m_sciq/train_job_output.txt
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/pythia-70m_sciq/train_job_output.txt
 #SBATCH --partition=sphinx
 #SBATCH --time=14-0
 
@@ -24,7 +24,7 @@ created following sbatch script:
 cd .
 
 # launch commands
-srun --unbuffered run_as_child_processes 'torchrun --master_port 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_4/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_4/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 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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'
 
 ###############################
 
@@ -34,461 +34,222 @@ submission to slurm complete!
 ###############################
 slurm submission output
 
-Submitted batch job 7597680
+
+
+sbatch: error: Batch job submission failed: Job dependency problem
+
+###############################
+
+slurm submission log: 2024-05-11 17:55:06.870798
+created following sbatch script: 
+
+###############################
+
+#!/bin/bash
+
+#SBATCH --account=nlp
+#SBATCH --cpus-per-task=16
+#SBATCH --dependency=afterok:7598872
+#SBATCH --gres=gpu:2
+#SBATCH --job-name=tthrush-job-4842885
+#SBATCH --mem=400G
+#SBATCH --nodelist=sphinx2
+#SBATCH --open-mode=append
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/pythia-70m_sciq/train_job_output.txt
+#SBATCH --partition=sphinx
+#SBATCH --time=14-0
+
+# activate your desired anaconda environment
+. /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 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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'
+
+###############################
+
+submission to slurm complete!
+
+
+###############################
+slurm submission output
+
+Submitted batch job 7598873
+
+
+
+###############################
+
+###############################
+start time: 2024-05-11 17:57:32.246511
+machine: sphinx2
+conda env: pretraining-coreset-selection
+###############################
+running following processes
+
+	torchrun --master_port 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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
+
+
+###############################
+command outputs: 
+
+
+[2024-05-11 17:57:34,935] torch.distributed.run: [WARNING] 
+[2024-05-11 17:57:34,935] torch.distributed.run: [WARNING] *****************************************
+[2024-05-11 17:57:34,935] 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. 
+[2024-05-11 17:57:34,935] torch.distributed.run: [WARNING] *****************************************
+05/11/2024 17:57:45 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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)
+05/11/2024 17:57:45 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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)
+Traceback (most recent call last):
+  File "/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_llm.py", line 202, in <module>
+    train_model()
+  File "/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_llm.py", line 162, in train_model
+    train_dataset = load_from_disk(script_args.dataset_id)
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/datasets/load.py", line 2638, in load_from_disk
+    raise FileNotFoundError(
+FileNotFoundError: Directory /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq is neither a `Dataset` directory nor a `DatasetDict` directory.
+Traceback (most recent call last):
+  File "/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_llm.py", line 202, in <module>
+    train_model()
+  File "/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_llm.py", line 162, in train_model
+    train_dataset = load_from_disk(script_args.dataset_id)
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/datasets/load.py", line 2638, in load_from_disk
+    raise FileNotFoundError(
+FileNotFoundError: Directory /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq is neither a `Dataset` directory nor a `DatasetDict` directory.
+[2024-05-11 17:57:49,960] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 3600439) of binary: /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/bin/python
+Traceback (most recent call last):
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/bin/torchrun", line 8, in <module>
+    sys.exit(main())
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
+    return f(*args, **kwargs)
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
+    run(args)
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
+    elastic_launch(
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
+    return launch_agent(self._config, self._entrypoint, list(args))
+  File "/nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 268, in launch_agent
+    raise ChildFailedError(
+torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
+============================================================
+train_llm.py FAILED
+------------------------------------------------------------
+Failures:
+[1]:
+  time      : 2024-05-11_17:57:49
+  host      : sphinx2.stanford.edu
+  rank      : 1 (local_rank: 1)
+  exitcode  : 1 (pid: 3600440)
+  error_file: <N/A>
+  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
+------------------------------------------------------------
+Root Cause (first observed failure):
+[0]:
+  time      : 2024-05-11_17:57:49
+  host      : sphinx2.stanford.edu
+  rank      : 0 (local_rank: 0)
+  exitcode  : 1 (pid: 3600439)
+  error_file: <N/A>
+  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
+============================================================
+###############################
+end time: 2024-05-11 17:57:52.272138
+elapsed time: 0:00:20.025627
+slurm submission log: 2024-05-11 18:01:39.581982
+created following sbatch script: 
+
+###############################
+
+#!/bin/bash
+
+#SBATCH --account=nlp
+#SBATCH --cpus-per-task=16
+#SBATCH --dependency=afterok:7598911
+#SBATCH --gres=gpu:2
+#SBATCH --job-name=tthrush-job-4293909
+#SBATCH --mem=400G
+#SBATCH --nodelist=sphinx2
+#SBATCH --open-mode=append
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/pythia-70m_sciq/train_job_output.txt
+#SBATCH --partition=sphinx
+#SBATCH --time=14-0
+
+# activate your desired anaconda environment
+. /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 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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'
+
+###############################
+
+submission to slurm complete!
+
+
+###############################
+slurm submission output
+
+Submitted batch job 7598912
 
 
 
 ###############################
 
 ###############################
-start time: 2024-05-11 11:12:34.797306
+start time: 2024-05-11 20:42:46.833506
 machine: sphinx2
 conda env: pretraining-coreset-selection
 ###############################
 running following processes
 
-	torchrun --master_port 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_4/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_4/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 29504 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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
 
 
 ###############################
 command outputs: 
 
 
-[2024-05-11 11:12:36,626] torch.distributed.run: [WARNING] 
-[2024-05-11 11:12:36,626] torch.distributed.run: [WARNING] *****************************************
-[2024-05-11 11:12:36,626] 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. 
-[2024-05-11 11:12:36,626] torch.distributed.run: [WARNING] *****************************************
-05/11/2024 11:12:43 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_4/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_4/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)
-05/11/2024 11:12:43 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_4/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_4/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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-[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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-
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  0%|          | 50/10682 [00:46<1:28:20,  2.01it/s]{'loss': 9.9791, 'grad_norm': 1.2299121618270874, 'learning_rate': 4.677268475210477e-05, 'epoch': 0.07}
-
                                                    

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                                                    {'loss': 9.257, 'grad_norm': 1.0650358200073242, 'learning_rate': 7.015902712815715e-05, 'epoch': 0.1}
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{'loss': 8.4555, 'grad_norm': 0.7713241577148438, 'learning_rate': 9.354536950420954e-05, 'epoch': 0.13}
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                                                     {'loss': 7.7979, 'grad_norm': 0.44380825757980347, 'learning_rate': 0.00011693171188026193, 'epoch': 0.16}
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                                                     {'loss': 7.2918, 'grad_norm': 0.41427773237228394, 'learning_rate': 0.0001403180542563143, 'epoch': 0.2}
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                                                     {'loss': 6.2093, 'grad_norm': 0.3936631977558136, 'learning_rate': 0.00021047708138447147, 'epoch': 0.29}
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                                                     {'loss': 5.9959, 'grad_norm': 0.5572906732559204, 'learning_rate': 0.00023386342376052386, 'epoch': 0.33}
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{'loss': 5.6731, 'grad_norm': 1.0436687469482422, 'learning_rate': 0.0002806361085126286, 'epoch': 0.39}
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                                                     {'loss': 5.5448, 'grad_norm': 0.5643438696861267, 'learning_rate': 0.00030402245088868103, 'epoch': 0.43}
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{'loss': 5.3244, 'grad_norm': 0.574114978313446, 'learning_rate': 0.0003507951356407858, 'epoch': 0.49}
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                                                     {'loss': 5.2346, 'grad_norm': 0.9441120028495789, 'learning_rate': 0.00037418147801683815, 'epoch': 0.52}
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{'loss': 5.1458, 'grad_norm': 0.5620614886283875, 'learning_rate': 0.0003975678203928906, 'epoch': 0.56}
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{'loss': 4.9904, 'grad_norm': 0.8300825953483582, 'learning_rate': 0.0004443405051449954, 'epoch': 0.62}
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{'loss': 4.9334, 'grad_norm': 0.5744912624359131, 'learning_rate': 0.0004677268475210477, 'epoch': 0.66}
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                                                     {'loss': 4.8722, 'grad_norm': 0.6070646643638611, 'learning_rate': 0.0004911131898971, 'epoch': 0.69}
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                                                     {'loss': 4.8024, 'grad_norm': 0.7427939772605896, 'learning_rate': 0.0005144995322731525, 'epoch': 0.72}
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{'loss': 4.7637, 'grad_norm': 0.4937581717967987, 'learning_rate': 0.0005378858746492049, 'epoch': 0.75}
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{'loss': 4.7039, 'grad_norm': 0.49991247057914734, 'learning_rate': 0.0005612722170252572, 'epoch': 0.79}
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                                                     {'loss': 4.6632, 'grad_norm': 0.46560388803482056, 'learning_rate': 0.0005846585594013096, 'epoch': 0.82}
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  6%|▌         | 650/10682 [05:43<1:22:36,  2.02it/s]{'loss': 4.6154, 'grad_norm': 0.5527864694595337, 'learning_rate': 0.0006080449017773621, 'epoch': 0.85}
                                                     
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                                                     {'loss': 4.5816, 'grad_norm': 0.5806276798248291, 'learning_rate': 0.0006314312441534145, 'epoch': 0.88}
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                                                     {'loss': 4.5486, 'grad_norm': 0.4780445098876953, 'learning_rate': 0.0006548175865294667, 'epoch': 0.92}
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                                                     {'loss': 4.5095, 'grad_norm': 0.501347005367279, 'learning_rate': 0.0006782039289055192, 'epoch': 0.95}
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                                                     {'loss': 4.4238, 'grad_norm': 0.4816618263721466, 'learning_rate': 0.0007249766136576241, 'epoch': 1.02}
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{'loss': 4.3809, 'grad_norm': 0.45101532340049744, 'learning_rate': 0.0007483629560336763, 'epoch': 1.05}
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  8%|▊         | 850/10682 [07:34<1:20:56,  2.02it/s]{'loss': 4.3347, 'grad_norm': 0.38607004284858704, 'learning_rate': 0.0007951356407857812, 'epoch': 1.11}
                                                     
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                                                     {'loss': 4.2726, 'grad_norm': 0.4214739203453064, 'learning_rate': 0.0008652946679139383, 'epoch': 1.21}
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  9%|▉         | 950/10682 [08:23<1:20:06,  2.02it/s]{'loss': 4.2514, 'grad_norm': 0.48058727383613586, 'learning_rate': 0.0008886810102899908, 'epoch': 1.25}
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                                                     {'loss': 4.243, 'grad_norm': 0.4515601694583893, 'learning_rate': 0.000912067352666043, 'epoch': 1.28}
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{'loss': 4.2199, 'grad_norm': 0.3445020020008087, 'learning_rate': 0.0009354536950420954, 'epoch': 1.31}
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                                                      {'loss': 4.1972, 'grad_norm': 0.36109039187431335, 'learning_rate': 0.0009588400374181479, 'epoch': 1.34}
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{'loss': 4.1839, 'grad_norm': 0.3835162818431854, 'learning_rate': 0.0009822263797942, 'epoch': 1.38}
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{'loss': 4.1558, 'grad_norm': 0.3170137107372284, 'learning_rate': 0.0009999990387768293, 'epoch': 1.41}
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                                                      {'loss': 4.1496, 'grad_norm': 0.4038255512714386, 'learning_rate': 0.0009999743408927195, 'epoch': 1.44}
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{'loss': 4.1212, 'grad_norm': 0.3136296570301056, 'learning_rate': 0.0009999162690918172, 'epoch': 1.47}
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                                                      {'loss': 4.1024, 'grad_norm': 0.3040776252746582, 'learning_rate': 0.0009998248272504882, 'epoch': 1.51}
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{'loss': 4.0825, 'grad_norm': 0.31836971640586853, 'learning_rate': 0.0009997000214725905, 'epoch': 1.54}
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                                                      {'loss': 4.0724, 'grad_norm': 0.2972266674041748, 'learning_rate': 0.000999541860089067, 'epoch': 1.57}
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                                                      {'loss': 4.0459, 'grad_norm': 0.3151179850101471, 'learning_rate': 0.0009993503536573894, 'epoch': 1.61}
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{'loss': 4.0342, 'grad_norm': 0.29821810126304626, 'learning_rate': 0.0009991255149608528, 'epoch': 1.64}
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                                                      {'loss': 4.0138, 'grad_norm': 0.2814204692840576, 'learning_rate': 0.0009988673590077238, 'epoch': 1.67}
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{'loss': 3.9806, 'grad_norm': 0.27087023854255676, 'learning_rate': 0.0009978931710439229, 'epoch': 1.77}
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                                                      {'loss': 3.9554, 'grad_norm': 0.26760560274124146, 'learning_rate': 0.000997501940608316, 'epoch': 1.8}
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{'loss': 3.9444, 'grad_norm': 0.25763311982154846, 'learning_rate': 0.0009970775012917489, 'epoch': 1.83}
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                                                      {'loss': 3.9307, 'grad_norm': 0.26242396235466003, 'learning_rate': 0.00099661988142608, 'epoch': 1.87}
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{'loss': 3.9184, 'grad_norm': 0.27897465229034424, 'learning_rate': 0.0009961291115580116, 'epoch': 1.9}
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{'loss': 3.9004, 'grad_norm': 0.26728904247283936, 'learning_rate': 0.0009956052244470509, 'epoch': 1.93}
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                                                      {'loss': 3.8887, 'grad_norm': 0.2725607454776764, 'learning_rate': 0.0009950482550633215, 'epoch': 1.97}
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                                                      {'loss': 3.8801, 'grad_norm': 0.2667035758495331, 'learning_rate': 0.0009944582405852314, 'epoch': 2.0}
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                                                      {'loss': 3.7545, 'grad_norm': 0.2644302248954773, 'learning_rate': 0.0009938352203969901, 'epoch': 2.03}
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{'loss': 3.7486, 'grad_norm': 0.26247215270996094, 'learning_rate': 0.0009931792360859792, 'epoch': 2.06}
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                                                      {'loss': 3.7567, 'grad_norm': 0.26597678661346436, 'learning_rate': 0.0009924903314399776, 'epoch': 2.1}
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                                                      {'loss': 3.7581, 'grad_norm': 0.2532075345516205, 'learning_rate': 0.0009917685524442382, 'epoch': 2.13}
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{'loss': 3.758, 'grad_norm': 0.24948535859584808, 'learning_rate': 0.0009910139472784174, 'epoch': 2.16}
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{'loss': 3.7511, 'grad_norm': 0.258324533700943, 'learning_rate': 0.0009902265663133602, 'epoch': 2.2}
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                                                      {'loss': 3.7414, 'grad_norm': 0.2505190670490265, 'learning_rate': 0.0009894064621077375, 'epoch': 2.23}
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                                                      {'loss': 3.7341, 'grad_norm': 0.25176048278808594, 'learning_rate': 0.0009885536894045377, 'epoch': 2.26}
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                                                      {'loss': 3.7315, 'grad_norm': 0.24798400700092316, 'learning_rate': 0.0009876683051274124, 'epoch': 2.29}
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                                                      {'loss': 3.7328, 'grad_norm': 0.2633359432220459, 'learning_rate': 0.0009867503683768772, 'epoch': 2.33}
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{'loss': 3.718, 'grad_norm': 0.2379371076822281, 'learning_rate': 0.0009848170847181403, 'epoch': 2.39}
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 17%|█▋        | 1850/10682 [16:01<1:12:35,  2.03it/s]{'loss': 3.7246, 'grad_norm': 0.2548748552799225, 'learning_rate': 0.0009838018668590573, 'epoch': 2.42}
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 18%|█▊        | 1875/10682 [16:13<1:13:04,  2.01it/s]{'loss': 3.7195, 'grad_norm': 0.26760780811309814, 'learning_rate': 0.000982754354616187, 'epoch': 2.46}
                                                      
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 18%|█▊        | 1900/10682 [16:26<1:13:18,  2.00it/s]{'loss': 3.7114, 'grad_norm': 0.2595493495464325, 'learning_rate': 0.0009816746179122904, 'epoch': 2.49}
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{'loss': 3.7051, 'grad_norm': 0.2557653784751892, 'learning_rate': 0.0009805627288211524, 'epoch': 2.52}
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{'loss': 3.7027, 'grad_norm': 0.25433629751205444, 'learning_rate': 0.0009794187615627694, 'epoch': 2.56}
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                                                      {'loss': 3.6958, 'grad_norm': 0.2566102147102356, 'learning_rate': 0.0009782427924983968, 'epoch': 2.59}
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{'loss': 3.6873, 'grad_norm': 0.25603529810905457, 'learning_rate': 0.00097703490012545, 'epoch': 2.62}
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 19%|█▉        | 2025/10682 [17:27<1:11:14,  2.03it/s]{'loss': 3.6868, 'grad_norm': 0.23180939257144928, 'learning_rate': 0.0009757951650722661, 'epoch': 2.65}
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{'loss': 3.6888, 'grad_norm': 0.23342260718345642, 'learning_rate': 0.0009732205000607044, 'epoch': 2.72}
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{'loss': 3.6693, 'grad_norm': 0.23111751675605774, 'learning_rate': 0.000971885741964458, 'epoch': 2.75}
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{'loss': 3.6675, 'grad_norm': 0.2428896725177765, 'learning_rate': 0.000964741322369231, 'epoch': 2.92}
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                                                      {'loss': 3.6434, 'grad_norm': 0.23653952777385712, 'learning_rate': 0.0009632189802949055, 'epoch': 2.95}
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{'loss': 3.6516, 'grad_norm': 0.24109138548374176, 'learning_rate': 0.0009616657177703876, 'epoch': 2.98}
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{'loss': 3.5007, 'grad_norm': 0.26071831583976746, 'learning_rate': 0.00095846684815675, 'epoch': 3.05}
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                                                      {'loss': 3.5089, 'grad_norm': 0.23226463794708252, 'learning_rate': 0.0009568214545962046, 'epoch': 3.08}
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                                                      {'loss': 3.5111, 'grad_norm': 0.23600921034812927, 'learning_rate': 0.0009551455676283627, 'epoch': 3.11}
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                                                      {'loss': 3.522, 'grad_norm': 0.23464976251125336, 'learning_rate': 0.0009534392991207893, 'epoch': 3.15}
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                                                      {'loss': 3.514, 'grad_norm': 0.24497349560260773, 'learning_rate': 0.0009517027629690559, 'epoch': 3.18}
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                                                      {'loss': 3.5099, 'grad_norm': 0.23021969199180603, 'learning_rate': 0.0009499360750891371, 'epoch': 3.21}
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                                                      {'loss': 3.5168, 'grad_norm': 0.2307622879743576, 'learning_rate': 0.0009481393534096735, 'epoch': 3.24}
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                                                      {'loss': 3.5267, 'grad_norm': 0.24119754135608673, 'learning_rate': 0.0009463127178640994, 'epoch': 3.28}
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                                                      {'loss': 3.5261, 'grad_norm': 0.23274315893650055, 'learning_rate': 0.0009444562903826375, 'epoch': 3.31}
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                                                      {'loss': 3.5214, 'grad_norm': 0.2249029278755188, 'learning_rate': 0.0009425701948841596, 'epoch': 3.34}
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                                                      {'loss': 3.5176, 'grad_norm': 0.23327051103115082, 'learning_rate': 0.0009406545572679153, 'epoch': 3.37}
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{'loss': 3.522, 'grad_norm': 0.24071739614009857, 'learning_rate': 0.0009367351691304569, 'epoch': 3.44}
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                                                      {'loss': 3.5182, 'grad_norm': 0.24651522934436798, 'learning_rate': 0.0009347316802333359, 'epoch': 3.47}
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{'loss': 3.5165, 'grad_norm': 0.2287723571062088, 'learning_rate': 0.0009326991724491712, 'epoch': 3.51}
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                                                      {'loss': 3.5162, 'grad_norm': 0.22941017150878906, 'learning_rate': 0.0009306377814504165, 'epoch': 3.54}
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                                                      {'loss': 3.5122, 'grad_norm': 0.24198299646377563, 'learning_rate': 0.0009285476448375166, 'epoch': 3.57}
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{'loss': 3.5187, 'grad_norm': 0.2328842133283615, 'learning_rate': 0.0009264289021297221, 'epoch': 3.6}
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                                                      {'loss': 3.511, 'grad_norm': 0.22649569809436798, 'learning_rate': 0.0009242816947557767, 'epoch': 3.64}
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                                                      {'loss': 3.5111, 'grad_norm': 0.24601294100284576, 'learning_rate': 0.0009221061660444758, 'epoch': 3.67}
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                                                      {'loss': 3.505, 'grad_norm': 0.22860173881053925, 'learning_rate': 0.0009176707273677235, 'epoch': 3.74}
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{'loss': 3.5152, 'grad_norm': 0.22003915905952454, 'learning_rate': 0.0009131237703641679, 'epoch': 3.8}
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{'loss': 3.4996, 'grad_norm': 0.24333731830120087, 'learning_rate': 0.0009108088507230948, 'epoch': 3.83}
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                                                      {'loss': 3.4947, 'grad_norm': 0.22305552661418915, 'learning_rate': 0.0009060969017710476, 'epoch': 3.9}
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{'loss': 3.4911, 'grad_norm': 0.2245049774646759, 'learning_rate': 0.0009037001869885992, 'epoch': 3.93}
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{'loss': 3.4916, 'grad_norm': 0.20952948927879333, 'learning_rate': 0.0009012765247103541, 'epoch': 3.96}
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                                                      {'loss': 3.4936, 'grad_norm': 0.253507137298584, 'learning_rate': 0.000898826076718821, 'epoch': 4.0}
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{'loss': 3.3653, 'grad_norm': 0.23862873017787933, 'learning_rate': 0.0008963490065844889, 'epoch': 4.03}
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                                                      {'loss': 3.3504, 'grad_norm': 0.23040835559368134, 'learning_rate': 0.0008938454796549082, 'epoch': 4.06}
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                                                      {'loss': 3.363, 'grad_norm': 0.24085748195648193, 'learning_rate': 0.000891315663043654, 'epoch': 4.1}
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{'loss': 3.3578, 'grad_norm': 0.23089420795440674, 'learning_rate': 0.0008887597256191701, 'epoch': 4.13}
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                                                      {'loss': 3.3698, 'grad_norm': 0.24029719829559326, 'learning_rate': 0.0008861778379934982, 'epoch': 4.16}
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{'loss': 3.3633, 'grad_norm': 0.23649613559246063, 'learning_rate': 0.000883570172510888, 'epoch': 4.19}
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                                                      {'loss': 3.3888, 'grad_norm': 0.24601532518863678, 'learning_rate': 0.0008782782059437559, 'epoch': 4.26}
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                                                      {'loss': 3.3857, 'grad_norm': 0.23610547184944153, 'learning_rate': 0.0008755942581046657, 'epoch': 4.29}
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                                                      {'loss': 3.3744, 'grad_norm': 0.2315978854894638, 'learning_rate': 0.0008728852388759212, 'epoch': 4.33}
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{'loss': 3.3804, 'grad_norm': 0.238857701420784, 'learning_rate': 0.0008701513290879668, 'epoch': 4.36}
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{'loss': 3.3825, 'grad_norm': 0.23522990942001343, 'learning_rate': 0.0008673927112327234, 'epoch': 4.39}
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                                                    {'loss': 3.3867, 'grad_norm': 0.22772274911403656, 'learning_rate': 0.0008618020895222331, 'epoch': 4.46}
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                                                    {'loss': 3.3965, 'grad_norm': 0.237548828125, 'learning_rate': 0.0008561148664436948, 'epoch': 4.52}
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                                                    {'loss': 3.3933, 'grad_norm': 0.23526379466056824, 'learning_rate': 0.0008532355029236307, 'epoch': 4.55}
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                                                    {'loss': 3.387, 'grad_norm': 0.2228415608406067, 'learning_rate': 0.0008474062329147856, 'epoch': 4.62}
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{'loss': 3.3923, 'grad_norm': 0.22207088768482208, 'learning_rate': 0.0008444567155371176, 'epoch': 4.65}
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                                                    {'loss': 3.3975, 'grad_norm': 0.23615622520446777, 'learning_rate': 0.000841484205239968, 'epoch': 4.69}
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{'loss': 3.3879, 'grad_norm': 0.2361529916524887, 'learning_rate': 0.0008384889004421422, 'epoch': 4.72}
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                                                    {'loss': 3.3874, 'grad_norm': 0.2185763120651245, 'learning_rate': 0.0008354710010840066, 'epoch': 4.75}
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                                                    {'loss': 3.3935, 'grad_norm': 0.2302001565694809, 'learning_rate': 0.0008324307086141438, 'epoch': 4.78}
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                                                    {'loss': 3.3914, 'grad_norm': 0.23731264472007751, 'learning_rate': 0.0008262837575938593, 'epoch': 4.85}
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                                                    {'loss': 3.3821, 'grad_norm': 0.22259749472141266, 'learning_rate': 0.0008231775093601584, 'epoch': 4.88}
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                                                    {'loss': 3.3928, 'grad_norm': 0.22700920701026917, 'learning_rate': 0.0008200496886207818, 'epoch': 4.91}
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{'loss': 3.39, 'grad_norm': 0.2216518372297287, 'learning_rate': 0.0008169005041617021, 'epoch': 4.95}
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{'loss': 3.3746, 'grad_norm': 0.2187589555978775, 'learning_rate': 0.0008137301661949477, 'epoch': 4.98}
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                                                    {'loss': 3.2307, 'grad_norm': 0.22435793280601501, 'learning_rate': 0.0008073268776325152, 'epoch': 5.05}
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                                                    {'loss': 3.2457, 'grad_norm': 0.2390066534280777, 'learning_rate': 0.0008040943544644116, 'epoch': 5.08}
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                                                    {'loss': 3.2426, 'grad_norm': 0.24324895441532135, 'learning_rate': 0.00080084153261525, 'epoch': 5.11}
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                                                    {'loss': 3.2569, 'grad_norm': 0.23969227075576782, 'learning_rate': 0.0007975686292149845, 'epoch': 5.14}
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{'loss': 3.2496, 'grad_norm': 0.23503965139389038, 'learning_rate': 0.0007942758627340383, 'epoch': 5.18}
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                                                    {'loss': 3.2625, 'grad_norm': 0.228496715426445, 'learning_rate': 0.00079096345296872, 'epoch': 5.21}
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                                                    {'loss': 3.2682, 'grad_norm': 0.23835501074790955, 'learning_rate': 0.0007842805893115124, 'epoch': 5.28}
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                                                    {'loss': 3.279, 'grad_norm': 0.2429271638393402, 'learning_rate': 0.0007809105815091867, 'epoch': 5.31}
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{'loss': 3.2764, 'grad_norm': 0.23455125093460083, 'learning_rate': 0.0007775218225718394, 'epoch': 5.34}
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{'loss': 3.2886, 'grad_norm': 0.25403472781181335, 'learning_rate': 0.0007741145387033967, 'epoch': 5.37}
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{'loss': 3.2859, 'grad_norm': 0.24228544533252716, 'learning_rate': 0.0007706889573443467, 'epoch': 5.41}
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                                                    {'loss': 3.2775, 'grad_norm': 0.2337915450334549, 'learning_rate': 0.0007637838180080183, 'epoch': 5.47}
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                                                    {'loss': 3.2846, 'grad_norm': 0.23796817660331726, 'learning_rate': 0.0007603047209574854, 'epoch': 5.5}
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{'loss': 3.287, 'grad_norm': 0.23975767195224762, 'learning_rate': 0.0007568082482390682, 'epoch': 5.54}
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                                                    {'loss': 3.2854, 'grad_norm': 0.2282705307006836, 'learning_rate': 0.0007532946332467235, 'epoch': 5.57}
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                                                    {'loss': 3.3005, 'grad_norm': 0.23405905067920685, 'learning_rate': 0.0007497641105186759, 'epoch': 5.6}
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{'loss': 3.2961, 'grad_norm': 0.22314269840717316, 'learning_rate': 0.0007462169157217631, 'epoch': 5.64}
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                                                    {'loss': 3.287, 'grad_norm': 0.22913289070129395, 'learning_rate': 0.0007426532856357045, 'epoch': 5.67}
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{'loss': 3.2899, 'grad_norm': 0.22870643436908722, 'learning_rate': 0.0007390734581372948, 'epoch': 5.7}
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                                                    {'loss': 3.2868, 'grad_norm': 0.23840422928333282, 'learning_rate': 0.0007354776721845277, 'epoch': 5.73}
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                                                    {'loss': 3.2924, 'grad_norm': 0.22819463908672333, 'learning_rate': 0.0007318661678006427, 'epoch': 5.77}
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                                                    {'loss': 3.299, 'grad_norm': 0.2298569679260254, 'learning_rate': 0.0007245969690625126, 'epoch': 5.83}
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                                                    {'loss': 3.2994, 'grad_norm': 0.22105765342712402, 'learning_rate': 0.0007209397599364363, 'epoch': 5.87}
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                                                    {'loss': 3.3022, 'grad_norm': 0.2392474263906479, 'learning_rate': 0.0007172678028031901, 'epoch': 5.9}
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                                                    {'loss': 3.307, 'grad_norm': 0.23637744784355164, 'learning_rate': 0.0007135813427705359, 'epoch': 5.93}
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                                                    {'loss': 3.2973, 'grad_norm': 0.22652505338191986, 'learning_rate': 0.0007061658992620613, 'epoch': 6.0}
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                                                    {'loss': 3.1398, 'grad_norm': 0.2383389174938202, 'learning_rate': 0.0006986954093387361, 'epoch': 6.06}
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                                                    {'loss': 3.1534, 'grad_norm': 0.24529814720153809, 'learning_rate': 0.0006949401447322816, 'epoch': 6.09}
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                                                    {'loss': 3.1615, 'grad_norm': 0.25546595454216003, 'learning_rate': 0.0006911718676257091, 'epoch': 6.13}
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{'loss': 3.1662, 'grad_norm': 0.23994998633861542, 'learning_rate': 0.0006873908295562602, 'epoch': 6.16}
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{'loss': 3.1653, 'grad_norm': 0.23644930124282837, 'learning_rate': 0.0006835972829129873, 'epoch': 6.19}
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                                                    {'loss': 3.1718, 'grad_norm': 0.24243521690368652, 'learning_rate': 0.000679791480919905, 'epoch': 6.23}
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                                                    {'loss': 3.1769, 'grad_norm': 0.23059093952178955, 'learning_rate': 0.000675973677619089, 'epoch': 6.26}
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                                                    {'loss': 3.1792, 'grad_norm': 0.23413194715976715, 'learning_rate': 0.0006721441278537161, 'epoch': 6.29}
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{'loss': 3.1772, 'grad_norm': 0.24112755060195923, 'learning_rate': 0.0006683030872510552, 'epoch': 6.32}
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                                                    {'loss': 3.1915, 'grad_norm': 0.23604540526866913, 'learning_rate': 0.0006644508122054031, 'epoch': 6.36}
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                                                    {'loss': 3.1908, 'grad_norm': 0.23378530144691467, 'learning_rate': 0.0006605875598609699, 'epoch': 6.39}
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                                                    {'loss': 3.2033, 'grad_norm': 0.250324547290802, 'learning_rate': 0.0006567135880947134, 'epoch': 6.42}
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{'loss': 3.1946, 'grad_norm': 0.23205330967903137, 'learning_rate': 0.0006528291554991272, 'epoch': 6.45}
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{'loss': 3.1994, 'grad_norm': 0.23225700855255127, 'learning_rate': 0.0006489345213649782, 'epoch': 6.49}
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{'loss': 3.2001, 'grad_norm': 0.2439790815114975, 'learning_rate': 0.0006450299456639985, 'epoch': 6.52}
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{'loss': 3.2009, 'grad_norm': 0.23067224025726318, 'learning_rate': 0.0006411156890315328, 'epoch': 6.55}
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                                                    {'loss': 3.2122, 'grad_norm': 0.22624000906944275, 'learning_rate': 0.0006371920127491398, 'epoch': 6.59}
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{'loss': 3.2027, 'grad_norm': 0.22114475071430206, 'learning_rate': 0.0006332591787271516, 'epoch': 6.62}
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                                                    {'loss': 3.2056, 'grad_norm': 0.25171154737472534, 'learning_rate': 0.0006293174494871916, 'epoch': 6.65}
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                                                    {'loss': 3.206, 'grad_norm': 0.2382051944732666, 'learning_rate': 0.0006253670881446494, 'epoch': 6.68}
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{'loss': 3.2115, 'grad_norm': 0.23231548070907593, 'learning_rate': 0.0006214083583911186, 'epoch': 6.72}
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                                                    {'loss': 3.2131, 'grad_norm': 0.23285098373889923, 'learning_rate': 0.0006174415244767953, 'epoch': 6.75}
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                                                    {'loss': 3.2105, 'grad_norm': 0.23752380907535553, 'learning_rate': 0.0006134668511928376, 'epoch': 6.78}
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{'loss': 3.2032, 'grad_norm': 0.2339238077402115, 'learning_rate': 0.0006094846038536922, 'epoch': 6.82}
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                                                    {'loss': 3.2151, 'grad_norm': 0.24121762812137604, 'learning_rate': 0.000605495048279383, 'epoch': 6.85}
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                                                    {'loss': 3.2086, 'grad_norm': 0.22973278164863586, 'learning_rate': 0.0006014984507777682, 'epoch': 6.88}
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                                                    {'loss': 3.2065, 'grad_norm': 0.24776624143123627, 'learning_rate': 0.000597495078126763, 'epoch': 6.91}
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                                                    {'loss': 3.2123, 'grad_norm': 0.22602494060993195, 'learning_rate': 0.000593485197556533, 'epoch': 6.95}
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{'loss': 3.0499, 'grad_norm': 0.24120673537254333, 'learning_rate': 0.0005773859555156823, 'epoch': 7.08}
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                                                    {'loss': 3.0714, 'grad_norm': 0.2382996678352356, 'learning_rate': 0.0005733475583803009, 'epoch': 7.11}
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                                                    {'loss': 3.0781, 'grad_norm': 0.23701493442058563, 'learning_rate': 0.0005693042652030427, 'epoch': 7.14}
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                                                    {'loss': 3.0915, 'grad_norm': 0.2366650253534317, 'learning_rate': 0.0005652563458788184, 'epoch': 7.18}
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                                                    {'loss': 3.0797, 'grad_norm': 0.247222438454628, 'learning_rate': 0.0005612040706113396, 'epoch': 7.21}
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{'loss': 3.1007, 'grad_norm': 0.2413272112607956, 'learning_rate': 0.0005571477098950832, 'epoch': 7.24}
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                                                    {'loss': 3.096, 'grad_norm': 0.23540514707565308, 'learning_rate': 0.0005530875344972343, 'epoch': 7.27}
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                                                    {'loss': 3.0979, 'grad_norm': 0.2377687394618988, 'learning_rate': 0.0005490238154396129, 'epoch': 7.31}
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{'loss': 3.1096, 'grad_norm': 0.23698937892913818, 'learning_rate': 0.0005449568239805831, 'epoch': 7.34}
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                                                    {'loss': 3.1068, 'grad_norm': 0.24594740569591522, 'learning_rate': 0.0005408868315969458, 'epoch': 7.37}
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                                                    {'loss': 3.1015, 'grad_norm': 0.2415093183517456, 'learning_rate': 0.0005368141099658168, 'epoch': 7.4}
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                                                    {'loss': 3.1121, 'grad_norm': 0.24498197436332703, 'learning_rate': 0.0005327389309464938, 'epoch': 7.44}
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                                                    {'loss': 3.1198, 'grad_norm': 0.2513814866542816, 'learning_rate': 0.0005286615665623071, 'epoch': 7.47}
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                                                    {'loss': 3.1255, 'grad_norm': 0.24393053352832794, 'learning_rate': 0.0005245822889824633, 'epoch': 7.5}
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                                                    {'loss': 3.1097, 'grad_norm': 0.2358766347169876, 'learning_rate': 0.0005205013705038776, 'epoch': 7.54}
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                                                    {'loss': 3.1254, 'grad_norm': 0.23983605206012726, 'learning_rate': 0.0005164190835329964, 'epoch': 7.57}
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                                                    {'loss': 3.1197, 'grad_norm': 0.2354630082845688, 'learning_rate': 0.0005123357005676156, 'epoch': 7.6}
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                                                    {'loss': 3.123, 'grad_norm': 0.2374172806739807, 'learning_rate': 0.0005082514941786895, 'epoch': 7.63}
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{'loss': 3.1158, 'grad_norm': 0.23482340574264526, 'learning_rate': 0.0005041667369921374, 'epoch': 7.67}
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{'loss': 3.1312, 'grad_norm': 0.2466896027326584, 'learning_rate': 0.0005000817016706441, 'epoch': 7.7}
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                                                    {'loss': 3.1325, 'grad_norm': 0.24224206805229187, 'learning_rate': 0.0004959966608954618, 'epoch': 7.73}
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{'loss': 3.1285, 'grad_norm': 0.23662075400352478, 'learning_rate': 0.0004919118873482054, 'epoch': 7.77}
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{'loss': 3.1199, 'grad_norm': 0.23915071785449982, 'learning_rate': 0.0004837442325565422, 'epoch': 7.83}
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                                                    {'loss': 3.1409, 'grad_norm': 0.23825491964817047, 'learning_rate': 0.00047966189651337725, 'epoch': 7.86}
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{'loss': 3.1259, 'grad_norm': 0.2457842230796814, 'learning_rate': 0.00047150156961954607, 'epoch': 7.93}
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{'loss': 3.1329, 'grad_norm': 0.25009796023368835, 'learning_rate': 0.0004674241234809751, 'epoch': 7.96}
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                                                    {'loss': 3.1389, 'grad_norm': 0.23241883516311646, 'learning_rate': 0.0004633488518231793, 'epoch': 7.99}
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{'loss': 3.0041, 'grad_norm': 0.24986298382282257, 'learning_rate': 0.00045927602667567333, 'epoch': 8.03}
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{'loss': 2.9736, 'grad_norm': 0.23748472332954407, 'learning_rate': 0.00045520591990466365, 'epoch': 8.06}
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{'loss': 2.9894, 'grad_norm': 0.25786739587783813, 'learning_rate': 0.00045113880319490264, 'epoch': 8.09}
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{'loss': 3.0012, 'grad_norm': 0.25063982605934143, 'learning_rate': 0.00044707494803155137, 'epoch': 8.13}
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                                                    {'loss': 3.004, 'grad_norm': 0.24591246247291565, 'learning_rate': 0.00044301462568205915, 'epoch': 8.16}
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                                                    {'loss': 2.995, 'grad_norm': 0.24545074999332428, 'learning_rate': 0.0004389581071780553, 'epoch': 8.19}
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                                                    {'loss': 3.0175, 'grad_norm': 0.24686549603939056, 'learning_rate': 0.0004349056632972576, 'epoch': 8.22}
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{'loss': 3.0103, 'grad_norm': 0.24353007972240448, 'learning_rate': 0.00043085756454539745, 'epoch': 8.26}
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                                                    {'loss': 3.0134, 'grad_norm': 0.2599690854549408, 'learning_rate': 0.0004268140811381641, 'epoch': 8.29}
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                                                    {'loss': 3.0201, 'grad_norm': 0.24743089079856873, 'learning_rate': 0.0004227754829831662, 'epoch': 8.32}
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{'loss': 3.0341, 'grad_norm': 0.2519805133342743, 'learning_rate': 0.0004187420396619156, 'epoch': 8.36}
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{'loss': 3.0345, 'grad_norm': 0.248518168926239, 'learning_rate': 0.00041471402041183287, 'epoch': 8.39}
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                                                    {'loss': 3.0441, 'grad_norm': 0.26396644115448, 'learning_rate': 0.0004066753292465861, 'epoch': 8.45}
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{'loss': 3.0432, 'grad_norm': 0.2469169944524765, 'learning_rate': 0.00040266519392417936, 'epoch': 8.49}
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                                                    {'loss': 3.0341, 'grad_norm': 0.24747087061405182, 'learning_rate': 0.00039866155582263653, 'epoch': 8.52}
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{'loss': 3.0497, 'grad_norm': 0.2444269061088562, 'learning_rate': 0.0003906748398221429, 'epoch': 8.58}
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{'loss': 3.0448, 'grad_norm': 0.24442660808563232, 'learning_rate': 0.00038271731370291583, 'epoch': 8.65}
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{'loss': 3.0541, 'grad_norm': 0.2559008300304413, 'learning_rate': 0.0003787501611262762, 'epoch': 8.68}
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{'loss': 3.0452, 'grad_norm': 0.24811796844005585, 'learning_rate': 0.0003747911021290519, 'epoch': 8.72}
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{'loss': 3.0514, 'grad_norm': 0.2517035901546478, 'learning_rate': 0.0003708404009834161, 'epoch': 8.75}
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                                                    {'loss': 3.0583, 'grad_norm': 0.2459789514541626, 'learning_rate': 0.00036296512652851323, 'epoch': 8.81}
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{'loss': 3.0477, 'grad_norm': 0.2461317926645279, 'learning_rate': 0.00035904107890373196, 'epoch': 8.85}
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                                                    {'loss': 3.0701, 'grad_norm': 0.24281562864780426, 'learning_rate': 0.00035512644046442116, 'epoch': 8.88}
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                                                    {'loss': 3.0496, 'grad_norm': 0.24403172731399536, 'learning_rate': 0.00034732643572487243, 'epoch': 8.94}
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{'loss': 3.0599, 'grad_norm': 0.24937552213668823, 'learning_rate': 0.000343441590084772, 'epoch': 8.98}
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                                                    {'loss': 2.9192, 'grad_norm': 0.24812904000282288, 'learning_rate': 0.0003318507897585944, 'epoch': 9.08}
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                                                      {'loss': 2.9346, 'grad_norm': 0.25665536522865295, 'learning_rate': 0.0003203610024806651, 'epoch': 9.17}
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{'loss': 2.9402, 'grad_norm': 0.2558586001396179, 'learning_rate': 0.0003165547155522783, 'epoch': 9.21}
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{'loss': 2.9594, 'grad_norm': 0.24871845543384552, 'learning_rate': 0.00030521033818340054, 'epoch': 9.31}
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{'loss': 2.9574, 'grad_norm': 0.26344871520996094, 'learning_rate': 0.0002977120114920343, 'epoch': 9.37}
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                                                      {'loss': 2.9609, 'grad_norm': 0.2551892101764679, 'learning_rate': 0.00029398297770374336, 'epoch': 9.4}
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                                                      {'loss': 2.9619, 'grad_norm': 0.252667635679245, 'learning_rate': 0.0002902676958110948, 'epoch': 9.44}
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                                                      {'loss': 2.9634, 'grad_norm': 0.2495369017124176, 'learning_rate': 0.0002865664138138335, 'epoch': 9.47}
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                                                      {'loss': 2.9631, 'grad_norm': 0.2484034299850464, 'learning_rate': 0.0002828793787771929, 'epoch': 9.5}
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                                                      {'loss': 2.9668, 'grad_norm': 0.24871808290481567, 'learning_rate': 0.0002792068368154043, 'epoch': 9.53}
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                                                      {'loss': 2.9674, 'grad_norm': 0.25618281960487366, 'learning_rate': 0.0002755490330752679, 'epoch': 9.57}
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                                                      {'loss': 2.9784, 'grad_norm': 0.2480897456407547, 'learning_rate': 0.00026827861591187944, 'epoch': 9.63}
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                                                      {'loss': 2.9739, 'grad_norm': 0.2510199546813965, 'learning_rate': 0.00026466648779812794, 'epoch': 9.67}
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                                                      {'loss': 2.9782, 'grad_norm': 0.24933770298957825, 'learning_rate': 0.0002610700684926339, 'epoch': 9.7}
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{'loss': 2.972, 'grad_norm': 0.2577074468135834, 'learning_rate': 0.00025392531550387867, 'epoch': 9.76}
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                                                      {'loss': 2.9878, 'grad_norm': 0.25236374139785767, 'learning_rate': 0.0002503774587418758, 'epoch': 9.8}
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{'loss': 2.9768, 'grad_norm': 0.24970197677612305, 'learning_rate': 0.00023983480588813622, 'epoch': 9.9}
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{'loss': 2.9799, 'grad_norm': 0.2499258816242218, 'learning_rate': 0.00023635500934422239, 'epoch': 9.93}
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                                                      {'loss': 2.8753, 'grad_norm': 0.25514543056488037, 'learning_rate': 0.00022602213475715589, 'epoch': 10.03}
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                                                      {'loss': 2.8651, 'grad_norm': 0.25445863604545593, 'learning_rate': 0.0002226141146140523, 'epoch': 10.06}
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{'loss': 2.8642, 'grad_norm': 0.2567098140716553, 'learning_rate': 0.00021922461032806601, 'epoch': 10.09}
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{'loss': 2.8753, 'grad_norm': 0.2543889880180359, 'learning_rate': 0.0002158538481528759, 'epoch': 10.12}
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                                                      {'loss': 2.8776, 'grad_norm': 0.25551044940948486, 'learning_rate': 0.00021250205309110155, 'epoch': 10.16}
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                                                      {'loss': 2.8798, 'grad_norm': 0.2618646025657654, 'learning_rate': 0.00020585625797294927, 'epoch': 10.22}
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{'loss': 2.8805, 'grad_norm': 0.2561207115650177, 'learning_rate': 0.00019928899940476624, 'epoch': 10.29}
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                                                      {'loss': 2.8919, 'grad_norm': 0.26057693362236023, 'learning_rate': 0.00019603537011569566, 'epoch': 10.32}
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                                                      {'loss': 2.901, 'grad_norm': 0.25939884781837463, 'learning_rate': 0.0001928020308484042, 'epoch': 10.35}
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                                                      {'loss': 2.8956, 'grad_norm': 0.2539978325366974, 'learning_rate': 0.00018958919743235897, 'epoch': 10.39}
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{'loss': 2.8982, 'grad_norm': 0.25841090083122253, 'learning_rate': 0.0001863970843282357, 'epoch': 10.42}
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{'loss': 2.8985, 'grad_norm': 0.2574446499347687, 'learning_rate': 0.00018007586996870206, 'epoch': 10.48}
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                                                      {'loss': 2.9064, 'grad_norm': 0.25932058691978455, 'learning_rate': 0.00017694719066230924, 'epoch': 10.52}
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{'loss': 2.9053, 'grad_norm': 0.26306411623954773, 'learning_rate': 0.00017384007553770858, 'epoch': 10.55}
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                                                      {'loss': 2.9027, 'grad_norm': 0.2599502503871918, 'learning_rate': 0.00017075473199874692, 'epoch': 10.58}
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{'loss': 2.9067, 'grad_norm': 0.2547256350517273, 'learning_rate': 0.00016769136599599017, 'epoch': 10.62}
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{'loss': 2.907, 'grad_norm': 0.2583419680595398, 'learning_rate': 0.00015863517062339038, 'epoch': 10.71}
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                                                      {'loss': 2.9076, 'grad_norm': 0.2581311762332916, 'learning_rate': 0.0001527113038415231, 'epoch': 10.78}
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                                                      {'loss': 2.9275, 'grad_norm': 0.26136869192123413, 'learning_rate': 0.00014978404491439802, 'epoch': 10.81}
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{'loss': 2.9017, 'grad_norm': 0.2525925040245056, 'learning_rate': 0.00014399985296581835, 'epoch': 10.88}
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                                                      {'loss': 2.9151, 'grad_norm': 0.2556012272834778, 'learning_rate': 0.00014114330604645943, 'epoch': 10.91}
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                                                      {'loss': 2.9214, 'grad_norm': 0.25660017132759094, 'learning_rate': 0.00013831071326327282, 'epoch': 10.94}
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{'loss': 2.92, 'grad_norm': 0.2554751932621002, 'learning_rate': 0.0001355022636953933, 'epoch': 10.98}
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                                                      {'loss': 2.8095, 'grad_norm': 0.2626868784427643, 'learning_rate': 0.0001272236408261237, 'epoch': 11.07}
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{'loss': 2.8251, 'grad_norm': 0.260630339384079, 'learning_rate': 0.00012451362249196797, 'epoch': 11.11}
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                                                      {'loss': 2.8319, 'grad_norm': 0.2583504021167755, 'learning_rate': 0.00011916895761319264, 'epoch': 11.17}
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                                                      {'loss': 2.8272, 'grad_norm': 0.25965994596481323, 'learning_rate': 0.0001165346678316832, 'epoch': 11.21}
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                                                      {'loss': 2.8423, 'grad_norm': 0.2596573233604431, 'learning_rate': 0.00011134305278348312, 'epoch': 11.27}
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                                                      {'loss': 2.8363, 'grad_norm': 0.26179489493370056, 'learning_rate': 0.00010878607406363367, 'epoch': 11.3}
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                                                      {'loss': 2.8465, 'grad_norm': 0.25883111357688904, 'learning_rate': 0.00010625520936593375, 'epoch': 11.34}
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                                                      {'loss': 2.8475, 'grad_norm': 0.26568856835365295, 'learning_rate': 0.0001037506276287885, 'epoch': 11.37}
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{'loss': 2.8419, 'grad_norm': 0.2595783472061157, 'learning_rate': 9.882098000652034e-05, 'epoch': 11.44}
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                                                      {'loss': 2.8497, 'grad_norm': 0.25906702876091003, 'learning_rate': 9.639624318158335e-05, 'epoch': 11.47}
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                                                      {'loss': 2.8471, 'grad_norm': 0.26192325353622437, 'learning_rate': 9.399844741560781e-05, 'epoch': 11.5}
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                                                      {'loss': 2.8461, 'grad_norm': 0.2596818506717682, 'learning_rate': 9.162775276448015e-05, 'epoch': 11.53}
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{'loss': 2.8502, 'grad_norm': 0.26064008474349976, 'learning_rate': 8.928431747505355e-05, 'epoch': 11.57}
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                                                      {'loss': 2.8442, 'grad_norm': 0.2584083378314972, 'learning_rate': 8.6968297974584e-05, 'epoch': 11.6}
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                                                      {'loss': 2.8474, 'grad_norm': 0.25908681750297546, 'learning_rate': 8.467984886028967e-05, 'epoch': 11.63}
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                                                      {'loss': 2.8517, 'grad_norm': 0.2583070695400238, 'learning_rate': 8.018627096711106e-05, 'epoch': 11.7}
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                                                      {'loss': 2.8577, 'grad_norm': 0.2627824544906616, 'learning_rate': 7.798144214020909e-05, 'epoch': 11.73}
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{'loss': 2.8482, 'grad_norm': 0.25886985659599304, 'learning_rate': 7.58047835834249e-05, 'epoch': 11.76}
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{'loss': 2.8536, 'grad_norm': 0.257649302482605, 'learning_rate': 6.94452730207023e-05, 'epoch': 11.86}
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                                                      {'loss': 2.8515, 'grad_norm': 0.25618743896484375, 'learning_rate': 6.738272954265156e-05, 'epoch': 11.89}
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                                                      {'loss': 2.8504, 'grad_norm': 0.25930941104888916, 'learning_rate': 6.534906381212979e-05, 'epoch': 11.93}
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{'loss': 2.8583, 'grad_norm': 0.2598854899406433, 'learning_rate': 6.334441157888504e-05, 'epoch': 11.96}
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{'loss': 2.8627, 'grad_norm': 0.2582871913909912, 'learning_rate': 6.1368906655978e-05, 'epoch': 11.99}
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{'loss': 2.812, 'grad_norm': 0.26445338129997253, 'learning_rate': 5.94226809108499e-05, 'epoch': 12.02}
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                                                      {'loss': 2.7947, 'grad_norm': 0.263980507850647, 'learning_rate': 5.7505864256519716e-05, 'epoch': 12.06}
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                                                      {'loss': 2.8025, 'grad_norm': 0.2615051567554474, 'learning_rate': 5.561858464291258e-05, 'epoch': 12.09}
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                                                      {'loss': 2.799, 'grad_norm': 0.26103320717811584, 'learning_rate': 5.193313847098613e-05, 'epoch': 12.16}
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                                                      {'loss': 2.7959, 'grad_norm': 0.2600698173046112, 'learning_rate': 4.836732641133895e-05, 'epoch': 12.22}
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                                                      {'loss': 2.7974, 'grad_norm': 0.25941604375839233, 'learning_rate': 4.492210053786228e-05, 'epoch': 12.29}
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{'loss': 2.8119, 'grad_norm': 0.2617456018924713, 'learning_rate': 4.3244996147050855e-05, 'epoch': 12.32}
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{'loss': 2.8065, 'grad_norm': 0.26041990518569946, 'learning_rate': 4.1598380727865315e-05, 'epoch': 12.35}
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                                                      {'loss': 2.7971, 'grad_norm': 0.2604943811893463, 'learning_rate': 3.998236419395806e-05, 'epoch': 12.39}
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{'loss': 2.8045, 'grad_norm': 0.2616060674190521, 'learning_rate': 3.839705441646779e-05, 'epoch': 12.42}
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{'loss': 2.8077, 'grad_norm': 0.262492299079895, 'learning_rate': 3.6842557216818006e-05, 'epoch': 12.45}
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{'loss': 2.8089, 'grad_norm': 0.2661857306957245, 'learning_rate': 3.531897635965431e-05, 'epoch': 12.48}
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{'loss': 2.8148, 'grad_norm': 0.2653377056121826, 'learning_rate': 3.382641354591731e-05, 'epoch': 12.52}
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{'loss': 2.8057, 'grad_norm': 0.2650749981403351, 'learning_rate': 3.093473849336781e-05, 'epoch': 12.58}
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                                                      {'loss': 2.8083, 'grad_norm': 0.25876399874687195, 'learning_rate': 2.9535819277506203e-05, 'epoch': 12.61}
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{'loss': 2.8049, 'grad_norm': 0.2628049850463867, 'learning_rate': 2.6832284358471516e-05, 'epoch': 12.68}
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                                                      {'loss': 2.8126, 'grad_norm': 0.26279115676879883, 'learning_rate': 2.5527849119658387e-05, 'epoch': 12.71}
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                                                      {'loss': 2.8055, 'grad_norm': 0.26302406191825867, 'learning_rate': 2.4255085494343522e-05, 'epoch': 12.75}
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                                                      {'loss': 2.82, 'grad_norm': 0.26460689306259155, 'learning_rate': 2.301407844110154e-05, 'epoch': 12.78}
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                                                      {'loss': 2.8083, 'grad_norm': 0.2638203799724579, 'learning_rate': 2.1804910798715826e-05, 'epoch': 12.81}
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                                                      {'loss': 2.8028, 'grad_norm': 0.25964269042015076, 'learning_rate': 2.0627663280649135e-05, 'epoch': 12.84}
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                                                      {'loss': 2.8117, 'grad_norm': 0.2623675763607025, 'learning_rate': 1.8369240812535104e-05, 'epoch': 12.91}
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{'loss': 2.8219, 'grad_norm': 0.2616770267486572, 'learning_rate': 1.7288216615031272e-05, 'epoch': 12.94}
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                                                      {'loss': 2.804, 'grad_norm': 0.2555890679359436, 'learning_rate': 1.6239414036870183e-05, 'epoch': 12.98}
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{'loss': 2.8038, 'grad_norm': 0.2590726912021637, 'learning_rate': 1.5222903086944684e-05, 'epoch': 13.01}
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                                                      {'loss': 2.7772, 'grad_norm': 0.2617104649543762, 'learning_rate': 1.3287025325307511e-05, 'epoch': 13.07}
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{'loss': 2.7842, 'grad_norm': 0.2624759078025818, 'learning_rate': 1.2367787735873993e-05, 'epoch': 13.11}
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                                                       {'loss': 2.7722, 'grad_norm': 0.2610248923301697, 'learning_rate': 1.1481100210606388e-05, 'epoch': 13.14}
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                                                       {'loss': 2.7839, 'grad_norm': 0.26264655590057373, 'learning_rate': 9.805609925895964e-06, 'epoch': 13.2}
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{'loss': 2.7802, 'grad_norm': 0.2598809599876404, 'learning_rate': 9.01691900753926e-06, 'epoch': 13.24}
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                                                       {'loss': 2.7716, 'grad_norm': 0.2618443965911865, 'learning_rate': 7.537908845868024e-06, 'epoch': 13.3}
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{'loss': 2.7848, 'grad_norm': 0.2590237855911255, 'learning_rate': 6.847688328344037e-06, 'epoch': 13.34}
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                                                       {'loss': 2.7796, 'grad_norm': 0.260278582572937, 'learning_rate': 6.190386348572108e-06, 'epoch': 13.37}
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                                                       {'loss': 2.7872, 'grad_norm': 0.2629893124103546, 'learning_rate': 4.974711304941093e-06, 'epoch': 13.43}
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                                                       {'loss': 2.7887, 'grad_norm': 0.2572675347328186, 'learning_rate': 4.416419388921844e-06, 'epoch': 13.47}
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{'loss': 2.7838, 'grad_norm': 0.25877076387405396, 'learning_rate': 3.891208300917604e-06, 'epoch': 13.5}
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                                                       {'loss': 2.7842, 'grad_norm': 0.2563156485557556, 'learning_rate': 3.3991130994299734e-06, 'epoch': 13.53}
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                                                       {'loss': 2.784, 'grad_norm': 0.2588604986667633, 'learning_rate': 2.940166632433183e-06, 'epoch': 13.56}
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{'loss': 2.7792, 'grad_norm': 0.26009050011634827, 'learning_rate': 2.5143995351817882e-06, 'epoch': 13.6}
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{'loss': 2.7916, 'grad_norm': 0.2611772119998932, 'learning_rate': 2.1218402281655835e-06, 'epoch': 13.63}
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{'loss': 2.7941, 'grad_norm': 0.2579527199268341, 'learning_rate': 1.7625149152127318e-06, 'epoch': 13.66}
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                                                       {'loss': 2.7732, 'grad_norm': 0.26120030879974365, 'learning_rate': 1.4364475817401635e-06, 'epoch': 13.7}
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                                                       {'loss': 2.7826, 'grad_norm': 0.25953397154808044, 'learning_rate': 1.143659993153079e-06, 'epoch': 13.73}
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{'loss': 2.7821, 'grad_norm': 0.25971662998199463, 'learning_rate': 8.841716933915555e-07, 'epoch': 13.76}
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                                                       {'loss': 2.7842, 'grad_norm': 0.26158714294433594, 'learning_rate': 4.651600211027507e-07, 'epoch': 13.83}
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                                                       {'loss': 2.7808, 'grad_norm': 0.2608095705509186, 'learning_rate': 3.0566461813213986e-07, 'epoch': 13.86}
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                                                       {'loss': 2.7874, 'grad_norm': 0.26148292422294617, 'learning_rate': 8.674791042273533e-08, 'epoch': 13.93}
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{'loss': 2.7847, 'grad_norm': 0.25786668062210083, 'learning_rate': 2.7341218649834522e-08, 'epoch': 13.96}
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                                                       {'loss': 2.7813, 'grad_norm': 0.2618885338306427, 'learning_rate': 1.3083313863404555e-09, 'epoch': 13.99}
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100%|██████████| 10682/10682 [1:31:48<00:00,  2.04it/s]{'train_runtime': 5519.626, 'train_samples_per_second': 1981.664, 'train_steps_per_second': 1.935, 'train_loss': 3.3957762572676518, 'epoch': 14.0}
                                                       
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-Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+[2024-05-11 20:42:48,810] torch.distributed.run: [WARNING] 
+[2024-05-11 20:42:48,810] torch.distributed.run: [WARNING] *****************************************
+[2024-05-11 20:42:48,810] 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. 
+[2024-05-11 20:42:48,810] torch.distributed.run: [WARNING] *****************************************
+05/11/2024 20:42:55 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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)
+05/11/2024 20:42:55 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_5/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_5/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)
+
  0%|          | 0/10682 [00:00<?, ?it/s][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())
+[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': 10.6527, 'grad_norm': 1.4306793212890625, 'learning_rate': 2.3386342376052384e-05, 'epoch': 0.03}
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{'loss': 7.7787, 'grad_norm': 0.4531400799751282, 'learning_rate': 0.00011693171188026193, 'epoch': 0.16}
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{'loss': 7.3082, 'grad_norm': 0.4752507507801056, 'learning_rate': 0.0001403180542563143, 'epoch': 0.2}
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{'loss': 6.9137, 'grad_norm': 0.5296725034713745, 'learning_rate': 0.00016370439663236668, 'epoch': 0.23}
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{'loss': 6.3124, 'grad_norm': 0.5124927759170532, 'learning_rate': 0.00021047708138447147, 'epoch': 0.29}
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                                                     {'loss': 5.9284, 'grad_norm': 1.1340378522872925, 'learning_rate': 0.00025724976613657625, 'epoch': 0.36}
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                                                     {'loss': 5.7957, 'grad_norm': 0.8028761744499207, 'learning_rate': 0.0002806361085126286, 'epoch': 0.39}
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                                                     {'loss': 5.6629, 'grad_norm': 0.5284114480018616, 'learning_rate': 0.00030402245088868103, 'epoch': 0.43}
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{'loss': 5.3617, 'grad_norm': 0.6408572793006897, 'learning_rate': 0.00037418147801683815, 'epoch': 0.52}
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                                                     {'loss': 5.2839, 'grad_norm': 0.6423079371452332, 'learning_rate': 0.0003975678203928906, 'epoch': 0.56}
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                                                     {'loss': 5.1951, 'grad_norm': 0.9615857005119324, 'learning_rate': 0.00042095416276894293, 'epoch': 0.59}
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                                                     {'loss': 5.1186, 'grad_norm': 0.9014081954956055, 'learning_rate': 0.0004443405051449954, 'epoch': 0.62}
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{'loss': 4.9916, 'grad_norm': 0.581803023815155, 'learning_rate': 0.0004911131898971, 'epoch': 0.69}
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                                                     {'loss': 4.9264, 'grad_norm': 0.9201842546463013, 'learning_rate': 0.0005144995322731525, 'epoch': 0.72}
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{'loss': 4.7288, 'grad_norm': 0.49271953105926514, 'learning_rate': 0.0006080449017773621, 'epoch': 0.85}
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  7%|▋         | 700/10682 [05:47<1:22:00,  2.03it/s]{'loss': 4.6572, 'grad_norm': 0.5065323710441589, 'learning_rate': 0.0006548175865294667, 'epoch': 0.92}
+
                                                     

  7%|▋         | 700/10682 [05:47<1:22:00,  2.03it/s]
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  7%|▋         | 725/10682 [06:00<1:21:46,  2.03it/s]{'loss': 4.614, 'grad_norm': 0.48452356457710266, 'learning_rate': 0.0006782039289055192, 'epoch': 0.95}
                                                     
+
  7%|▋         | 725/10682 [06:00<1:21:46,  2.03it/s]
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  7%|▋         | 750/10682 [06:12<1:21:32,  2.03it/s]{'loss': 4.5681, 'grad_norm': 0.47516340017318726, 'learning_rate': 0.0007015902712815716, 'epoch': 0.98}
+
                                                     

  7%|▋         | 750/10682 [06:12<1:21:32,  2.03it/s]
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  7%|▋         | 775/10682 [06:36<1:33:11,  1.77it/s]{'loss': 4.5174, 'grad_norm': 0.6032619476318359, 'learning_rate': 0.0007249766136576241, 'epoch': 1.02}
+
                                                     

  7%|▋         | 775/10682 [06:36<1:33:11,  1.77it/s]
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