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: 2024-05-20 10:11:55.099041
+slurm submission log: 2024-05-20 23:23:34.591873
 created following sbatch script: 
 
 ###############################
@@ -7,13 +7,13 @@ created following sbatch script:
 
 #SBATCH --account=nlp
 #SBATCH --cpus-per-task=16
-#SBATCH --dependency=afterok:7635777
+#SBATCH --dependency=afterok:7637763
 #SBATCH --gres=gpu:2
-#SBATCH --job-name=tthrush-job-2917184
+#SBATCH --job-name=tthrush-job-4809586
 #SBATCH --mem=100G
 #SBATCH --nodelist=sphinx2
 #SBATCH --open-mode=append
-#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/70m_llms_more_data_test_normalized/pythia-70m_sciq_1/train_job_output.txt
+#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/llms/pythia-70m_sciq_1/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_more_data_test_normalized/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/70m_llms_more_data_test_normalized/pythia-70m_sciq_1 --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2 --per_device_train_batch_size 256 --seed 1 --num_train_epochs 1'
+srun --unbuffered run_as_child_processes 'torchrun --master_port 29524 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/data/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/llms/pythia-70m_sciq_1 --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2 --per_device_train_batch_size 256 --seed 1 --num_train_epochs 1'
 
 ###############################
 
@@ -34,13 +34,13 @@ submission to slurm complete!
 ###############################
 slurm submission output
 
-Submitted batch job 7635778
+Submitted batch job 7637764
 
 
 
 ###############################
 
-/var/lib/slurm/slurmd/job7635778/slurm_script: line 16: /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/etc/profile.d/conda.sh: No such file or directory
+/var/lib/slurm/slurmd/job7637764/slurm_script: line 16: /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/etc/profile.d/conda.sh: No such file or directory
 
 CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
 To initialize your shell, run
@@ -61,454 +61,455 @@ IMPORTANT: You may need to close and restart your shell after running 'conda ini
 
 
 ###############################
-start time: 2024-05-20 12:05:58.376173
+start time: 2024-05-21 03:31:28.384617
 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_more_data_test_normalized/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/70m_llms_more_data_test_normalized/pythia-70m_sciq_1 --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2 --per_device_train_batch_size 256 --seed 1 --num_train_epochs 1
+	torchrun --master_port 29524 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/data/sciq --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/llms/pythia-70m_sciq_1 --output_hub_id pythia-70m_sciq --model_id EleutherAI/pythia-70m --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2 --per_device_train_batch_size 256 --seed 1 --num_train_epochs 1
 
 
 ###############################
 command outputs: 
 
 
-[2024-05-20 12:06:00,524] torch.distributed.run: [WARNING] 
-[2024-05-20 12:06:00,524] torch.distributed.run: [WARNING] *****************************************
-[2024-05-20 12:06:00,524] 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. 
-[2024-05-20 12:06:00,524] torch.distributed.run: [WARNING] *****************************************
-05/20/2024 12:06:06 - INFO - __main__ - Script parameters ScriptArguments(seed=1, dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data_test_normalized/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/70m_llms_more_data_test_normalized/pythia-70m_sciq_1', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1.0, 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)
-05/20/2024 12:06:11 - INFO - __main__ - Script parameters ScriptArguments(seed=1, dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data_test_normalized/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/70m_llms_more_data_test_normalized/pythia-70m_sciq_1', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1.0, 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%|          | 0/10696 [00:00<?, ?it/s][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())
+[2024-05-21 03:31:32,581] torch.distributed.run: [WARNING] 
+[2024-05-21 03:31:32,581] torch.distributed.run: [WARNING] *****************************************
+[2024-05-21 03:31:32,581] 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. 
+[2024-05-21 03:31:32,581] torch.distributed.run: [WARNING] *****************************************
+05/21/2024 03:31:41 - INFO - __main__ - Script parameters ScriptArguments(seed=1, dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/data/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/llms/pythia-70m_sciq_1', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1.0, 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)
+05/21/2024 03:31:41 - INFO - __main__ - Script parameters ScriptArguments(seed=1, dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/data/sciq', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/test_ordinal_clipped_scaled_mean/llms/pythia-70m_sciq_1', output_hub_id='pythia-70m_sciq', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1.0, 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%|          | 0/10712 [00:00<?, ?it/s][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())
 [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': 10.6585, 'grad_norm': 1.433795690536499, 'learning_rate': 2.336448598130841e-05, 'epoch': 0.0}
-
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-
                                                     

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{'loss': 9.2091, 'grad_norm': 1.128482699394226, 'learning_rate': 7.009345794392523e-05, 'epoch': 0.01}
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-
                                                     

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{'loss': 7.3176, 'grad_norm': 0.5299851298332214, 'learning_rate': 0.00014018691588785047, 'epoch': 0.01}
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{'loss': 6.3821, 'grad_norm': 0.4912753403186798, 'learning_rate': 0.0002102803738317757, 'epoch': 0.02}
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                                                     {'loss': 5.8905, 'grad_norm': 0.7734078168869019, 'learning_rate': 0.00028037383177570094, 'epoch': 0.03}
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{'loss': 5.7595, 'grad_norm': 0.5843368768692017, 'learning_rate': 0.00030373831775700936, 'epoch': 0.03}
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  4%|▎         | 375/10696 [25:34<11:28:51,  4.00s/it]{'loss': 5.5639, 'grad_norm': 0.5673643350601196, 'learning_rate': 0.00035046728971962614, 'epoch': 0.04}
                                                      
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  4%|▎         | 400/10696 [26:59<6:34:42,  2.30s/it]{'loss': 5.4725, 'grad_norm': 0.6777312755584717, 'learning_rate': 0.00037383177570093456, 'epoch': 0.04}
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  4%|▍         | 425/10696 [28:09<6:58:01,  2.44s/it]{'loss': 5.3951, 'grad_norm': 0.7804048657417297, 'learning_rate': 0.000397196261682243, 'epoch': 0.04}
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  4%|▍         | 450/10696 [28:59<4:15:00,  1.49s/it]{'loss': 5.3206, 'grad_norm': 0.6993443965911865, 'learning_rate': 0.0004205607476635514, 'epoch': 0.04}
                                                     
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  4%|▍         | 475/10696 [29:45<3:48:54,  1.34s/it]{'loss': 5.264, 'grad_norm': 0.6879208087921143, 'learning_rate': 0.0004439252336448598, 'epoch': 0.04}
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  5%|▍         | 525/10696 [30:24<1:59:12,  1.42it/s]{'loss': 5.136, 'grad_norm': 0.5651555061340332, 'learning_rate': 0.0004906542056074767, 'epoch': 0.05}
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  5%|▌         | 550/10696 [30:43<2:14:26,  1.26it/s]{'loss': 5.0904, 'grad_norm': 0.442416787147522, 'learning_rate': 0.000514018691588785, 'epoch': 0.05}
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{'loss': 5.0425, 'grad_norm': 0.5118783116340637, 'learning_rate': 0.0005373831775700935, 'epoch': 0.05}
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{'loss': 4.8367, 'grad_norm': 0.4248983561992645, 'learning_rate': 0.0006542056074766354, 'epoch': 0.07}
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{'loss': 4.6914, 'grad_norm': 0.3979177176952362, 'learning_rate': 0.0007710280373831776, 'epoch': 0.08}
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{'loss': 4.6215, 'grad_norm': 0.3325541913509369, 'learning_rate': 0.0008411214953271028, 'epoch': 0.08}
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{'loss': 4.5261, 'grad_norm': 0.3472473621368408, 'learning_rate': 0.000957943925233645, 'epoch': 0.1}
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                                                      {'loss': 4.482, 'grad_norm': 0.32362473011016846, 'learning_rate': 0.0009999993342855993, 'epoch': 0.1}
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{'loss': 4.4671, 'grad_norm': 0.3064156770706177, 'learning_rate': 0.0009999760344677087, 'epoch': 0.1}
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{'loss': 4.3888, 'grad_norm': 0.2892473042011261, 'learning_rate': 0.000999550044468137, 'epoch': 0.11}
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{'loss': 4.3772, 'grad_norm': 0.31722646951675415, 'learning_rate': 0.0009993603847347483, 'epoch': 0.11}
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{'loss': 4.3076, 'grad_norm': 0.257009893655777, 'learning_rate': 0.0009979137715755973, 'epoch': 0.13}
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{'loss': 4.2271, 'grad_norm': 0.2521156668663025, 'learning_rate': 0.0009950844505907288, 'epoch': 0.14}
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{'loss': 4.2045, 'grad_norm': 0.26081693172454834, 'learning_rate': 0.000993224404331956, 'epoch': 0.15}
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                                                      {'loss': 4.1618, 'grad_norm': 0.2582828998565674, 'learning_rate': 0.0009894682971706937, 'epoch': 0.16}
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 16%|█▌        | 1725/10696 [40:44<1:14:16,  2.01it/s]{'loss': 4.1665, 'grad_norm': 0.23643942177295685, 'learning_rate': 0.0009886191115052376, 'epoch': 0.16}
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 16%|█▋        | 1750/10696 [40:57<1:14:04,  2.01it/s]{'loss': 4.1484, 'grad_norm': 0.22036579251289368, 'learning_rate': 0.000987737397935119, 'epoch': 0.16}
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 17%|█▋        | 1775/10696 [41:10<1:15:21,  1.97it/s]{'loss': 4.1402, 'grad_norm': 0.23759111762046814, 'learning_rate': 0.0009868232151569668, 'epoch': 0.17}
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 17%|█▋        | 1800/10696 [41:22<1:13:32,  2.02it/s]{'loss': 4.1346, 'grad_norm': 0.23659701645374298, 'learning_rate': 0.0009858766240289217, 'epoch': 0.17}
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 17%|█▋        | 1825/10696 [41:35<1:13:22,  2.02it/s]{'loss': 4.1434, 'grad_norm': 0.23220054805278778, 'learning_rate': 0.0009848976875665818, 'epoch': 0.17}
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{'loss': 4.121, 'grad_norm': 0.2492087334394455, 'learning_rate': 0.0009838864709388105, 'epoch': 0.17}
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 18%|█▊        | 1875/10696 [42:00<1:13:26,  2.00it/s]{'loss': 4.1132, 'grad_norm': 0.2613946795463562, 'learning_rate': 0.0009828430414633963, 'epoch': 0.18}
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 18%|█▊        | 1889/10696 [42:06<1:12:49,  2.02it/s]
 18%|█▊        | 1890/10696 [42:07<1:12:46,  2.02it/s]
 18%|█▊        | 1891/10696 [42:07<1:12:53,  2.01it/s]
 18%|█▊        | 1892/10696 [42:08<1:12:52,  2.01it/s]
 18%|█▊        | 1893/10696 [42:08<1:12:46,  2.02it/s]
 18%|█▊        | 1894/10696 [42:09<1:12:48,  2.01it/s]
 18%|█▊        | 1895/10696 [42:09<1:12:44,  2.02it/s]
 18%|█▊        | 1896/10696 [42:10<1:12:45,  2.02it/s]
 18%|█▊        | 1897/10696 [42:10<1:12:41,  2.02it/s]
 18%|█▊        | 1898/10696 [42:11<1:12:44,  2.02it/s]
 18%|█▊        | 1899/10696 [42:11<1:12:40,  2.02it/s]
 18%|█▊        | 1900/10696 [42:12<1:12:44,  2.02it/s]{'loss': 4.111, 'grad_norm': 0.23352862894535065, 'learning_rate': 0.0009817674686025723, 'epoch': 0.18}
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 18%|█▊        | 1900/10696 [42:12<1:12:44,  2.02it/s]
 18%|█▊        | 1901/10696 [42:12<1:12:51,  2.01it/s]
 18%|█▊        | 1902/10696 [42:13<1:12:48,  2.01it/s]
 18%|█▊        | 1903/10696 [42:13<1:12:48,  2.01it/s]
 18%|█▊        | 1904/10696 [42:14<1:12:41,  2.02it/s]
 18%|█▊        | 1905/10696 [42:14<1:12:44,  2.01it/s]
 18%|█▊        | 1906/10696 [42:15<1:12:43,  2.01it/s]
 18%|█▊        | 1907/10696 [42:15<1:12:39,  2.02it/s]
 18%|█▊        | 1908/10696 [42:16<1:12:43,  2.01it/s]
 18%|█▊        | 1909/10696 [42:16<1:12:37,  2.02it/s]
 18%|█▊        | 1910/10696 [42:17<1:12:38,  2.02it/s]
 18%|█▊        | 1911/10696 [42:17<1:12:35,  2.02it/s]
 18%|█▊        | 1912/10696 [42:18<1:12:37,  2.02it/s]
 18%|█▊        | 1913/10696 [42:18<1:12:46,  2.01it/s]
 18%|█▊        | 1914/10696 [42:19<1:12:40,  2.01it/s]
 18%|█▊        | 1915/10696 [42:19<1:12:43,  2.01it/s]
 18%|█▊        | 1916/10696 [42:20<1:12:40,  2.01it/s]
 18%|█▊        | 1917/10696 [42:20<1:12:36,  2.02it/s]
 18%|█▊        | 1918/10696 [42:21<1:12:32,  2.02it/s]
 18%|█▊        | 1919/10696 [42:21<1:12:32,  2.02it/s]
 18%|█▊        | 1920/10696 [42:22<1:12:30,  2.02it/s]
 18%|█▊        | 1921/10696 [42:22<1:12:29,  2.02it/s]
 18%|█▊        | 1922/10696 [42:23<1:12:31,  2.02it/s]
 18%|█▊        | 1923/10696 [42:23<1:12:27,  2.02it/s]
 18%|█▊        | 1924/10696 [42:24<1:12:32,  2.02it/s]
 18%|█▊        | 1925/10696 [42:24<1:12:28,  2.02it/s]{'loss': 4.1037, 'grad_norm': 0.2406768500804901, 'learning_rate': 0.0009806598239583907, 'epoch': 0.18}
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 18%|█▊        | 1925/10696 [42:24<1:12:28,  2.02it/s]
 18%|█▊        | 1926/10696 [42:25<1:12:36,  2.01it/s]
 18%|█▊        | 1927/10696 [42:25<1:12:31,  2.02it/s]
 18%|█▊        | 1928/10696 [42:26<1:13:36,  1.99it/s]
 18%|█▊        | 1929/10696 [42:26<1:13:17,  1.99it/s]
 18%|█▊        | 1930/10696 [42:27<1:13:01,  2.00it/s]
 18%|█▊        | 1931/10696 [42:27<1:12:49,  2.01it/s]
 18%|█▊        | 1932/10696 [42:28<1:12:43,  2.01it/s]
 18%|█▊        | 1933/10696 [42:28<1:12:36,  2.01it/s]
 18%|█▊        | 1934/10696 [42:29<1:12:37,  2.01it/s]
 18%|█▊        | 1935/10696 [42:29<1:12:29,  2.01it/s]
 18%|█▊        | 1936/10696 [42:30<1:12:33,  2.01it/s]
 18%|█▊        | 1937/10696 [42:30<1:12:27,  2.01it/s]
 18%|█▊        | 1938/10696 [42:31<1:12:26,  2.01it/s]
 18%|█▊        | 1939/10696 [42:31<1:12:27,  2.01it/s]
 18%|█▊        | 1940/10696 [42:32<1:12:27,  2.01it/s]
 18%|█▊        | 1941/10696 [42:32<1:12:24,  2.02it/s]
 18%|█▊        | 1942/10696 [42:33<1:12:22,  2.02it/s]
 18%|█▊        | 1943/10696 [42:33<1:12:27,  2.01it/s]
 18%|█▊        | 1944/10696 [42:34<1:12:22,  2.02it/s]
 18%|█▊        | 1945/10696 [42:34<1:12:25,  2.01it/s]
 18%|█▊        | 1946/10696 [42:35<1:12:20,  2.02it/s]
 18%|█▊        | 1947/10696 [42:35<1:12:21,  2.02it/s]
 18%|█▊        | 1948/10696 [42:36<1:12:23,  2.01it/s]
 18%|█▊        | 1949/10696 [42:36<1:12:23,  2.01it/s]
 18%|█▊        | 1950/10696 [42:37<1:12:22,  2.01it/s]{'loss': 4.0966, 'grad_norm': 0.22319981455802917, 'learning_rate': 0.0009795201812679588, 'epoch': 0.18}
-
                                                      

 18%|█▊        | 1950/10696 [42:37<1:12:22,  2.01it/s]
 18%|█▊        | 1951/10696 [42:37<1:13:22,  1.99it/s]
 18%|█▊        | 1952/10696 [42:38<1:13:02,  2.00it/s]
 18%|█▊        | 1953/10696 [42:38<1:12:44,  2.00it/s]
 18%|█▊        | 1954/10696 [42:39<1:12:45,  2.00it/s]
 18%|█▊        | 1955/10696 [42:39<1:12:38,  2.01it/s]
 18%|█▊        | 1956/10696 [42:40<1:12:30,  2.01it/s]
 18%|█▊        | 1957/10696 [42:40<1:13:19,  1.99it/s]
 18%|█▊        | 1958/10696 [42:41<1:12:54,  2.00it/s]
 18%|█▊        | 1959/10696 [42:41<1:12:47,  2.00it/s]
 18%|█▊        | 1960/10696 [42:42<1:12:30,  2.01it/s]
 18%|█▊        | 1961/10696 [42:42<1:12:26,  2.01it/s]
 18%|█▊        | 1962/10696 [42:43<1:12:16,  2.01it/s]
 18%|█▊        | 1963/10696 [42:43<1:12:15,  2.01it/s]
 18%|█▊        | 1964/10696 [42:44<1:12:18,  2.01it/s]
 18%|█▊        | 1965/10696 [42:44<1:12:16,  2.01it/s]
 18%|█▊        | 1966/10696 [42:45<1:12:14,  2.01it/s]
 18%|█▊        | 1967/10696 [42:45<1:12:11,  2.02it/s]
 18%|█▊        | 1968/10696 [42:46<1:12:14,  2.01it/s]
 18%|█▊        | 1969/10696 [42:46<1:12:13,  2.01it/s]
 18%|█▊        | 1970/10696 [42:47<1:12:14,  2.01it/s]
 18%|█▊        | 1971/10696 [42:47<1:12:08,  2.02it/s]
 18%|█▊        | 1972/10696 [42:48<1:12:09,  2.01it/s]
 18%|█▊        | 1973/10696 [42:48<1:12:09,  2.01it/s]
 18%|█▊        | 1974/10696 [42:49<1:12:10,  2.01it/s]
 18%|█▊        | 1975/10696 [42:49<1:12:14,  2.01it/s]{'loss': 4.0882, 'grad_norm': 0.22948966920375824, 'learning_rate': 0.0009783486163985268, 'epoch': 0.18}
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 18%|█▊        | 1975/10696 [42:49<1:12:14,  2.01it/s]
 18%|█▊        | 1976/10696 [42:50<1:12:21,  2.01it/s]
 18%|█▊        | 1977/10696 [42:50<1:12:15,  2.01it/s]
 18%|█▊        | 1978/10696 [42:51<1:12:15,  2.01it/s]
 19%|█▊        | 1979/10696 [42:51<1:12:08,  2.01it/s]
 19%|█▊        | 1980/10696 [42:52<1:12:06,  2.01it/s]
 19%|█▊        | 1981/10696 [42:52<1:12:00,  2.02it/s]
 19%|█▊        | 1982/10696 [42:53<1:12:03,  2.02it/s]
 19%|█▊        | 1983/10696 [42:53<1:12:00,  2.02it/s]
 19%|█▊        | 1984/10696 [42:54<1:12:02,  2.02it/s]
 19%|█▊        | 1985/10696 [42:54<1:12:01,  2.02it/s]
 19%|█▊        | 1986/10696 [42:55<1:12:00,  2.02it/s]
 19%|█▊        | 1987/10696 [42:55<1:11:57,  2.02it/s]
 19%|█▊        | 1988/10696 [42:56<1:11:59,  2.02it/s]
 19%|█▊        | 1989/10696 [42:56<1:12:02,  2.01it/s]
 19%|█▊        | 1990/10696 [42:57<1:11:58,  2.02it/s]
 19%|█▊        | 1991/10696 [42:57<1:12:00,  2.01it/s]
 19%|█▊        | 1992/10696 [42:58<1:11:59,  2.01it/s]
 19%|█▊        | 1993/10696 [42:58<1:12:03,  2.01it/s]
 19%|█▊        | 1994/10696 [42:59<1:12:07,  2.01it/s]
 19%|█▊        | 1995/10696 [42:59<1:12:04,  2.01it/s]
 19%|█▊        | 1996/10696 [43:00<1:12:00,  2.01it/s]
 19%|█▊        | 1997/10696 [43:00<1:11:57,  2.01it/s]
 19%|█▊        | 1998/10696 [43:01<1:11:56,  2.02it/s]
 19%|█▊        | 1999/10696 [43:01<1:11:55,  2.02it/s]
 19%|█▊        | 2000/10696 [43:02<1:11:49,  2.02it/s]{'loss': 4.0826, 'grad_norm': 0.23388968408107758, 'learning_rate': 0.0009771452073424405, 'epoch': 0.19}
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 19%|█▊        | 2000/10696 [43:02<1:11:49,  2.02it/s]
 19%|█▊        | 2001/10696 [43:02<1:13:16,  1.98it/s]
 19%|█▊        | 2002/10696 [43:03<1:12:51,  1.99it/s]
 19%|█▊        | 2003/10696 [43:03<1:12:35,  2.00it/s]
 19%|█▊        | 2004/10696 [43:04<1:12:21,  2.00it/s]
 19%|█▊        | 2005/10696 [43:04<1:12:11,  2.01it/s]
 19%|█▉        | 2006/10696 [43:05<1:12:09,  2.01it/s]
 19%|█▉        | 2007/10696 [43:05<1:12:06,  2.01it/s]
 19%|█▉        | 2008/10696 [43:06<1:12:03,  2.01it/s]
 19%|█▉        | 2009/10696 [43:06<1:12:01,  2.01it/s]
 19%|█▉        | 2010/10696 [43:07<1:11:55,  2.01it/s]
 19%|█▉        | 2011/10696 [43:07<1:11:55,  2.01it/s]
 19%|█▉        | 2012/10696 [43:08<1:11:48,  2.02it/s]
 19%|█▉        | 2013/10696 [43:08<1:11:48,  2.02it/s]
 19%|█▉        | 2014/10696 [43:09<1:11:41,  2.02it/s]
 19%|█▉        | 2015/10696 [43:09<1:11:46,  2.02it/s]
 19%|█▉        | 2016/10696 [43:10<1:11:43,  2.02it/s]
 19%|█▉        | 2017/10696 [43:10<1:11:48,  2.01it/s]
 19%|█▉        | 2018/10696 [43:11<1:11:45,  2.02it/s]
 19%|█▉        | 2019/10696 [43:11<1:11:48,  2.01it/s]
 19%|█▉        | 2020/10696 [43:12<1:11:46,  2.01it/s]
 19%|█▉        | 2021/10696 [43:12<1:11:47,  2.01it/s]
 19%|█▉        | 2022/10696 [43:13<1:11:40,  2.02it/s]
 19%|█▉        | 2023/10696 [43:13<1:11:41,  2.02it/s]
 19%|█▉        | 2024/10696 [43:14<1:11:36,  2.02it/s]
 19%|█▉        | 2025/10696 [43:14<1:11:41,  2.02it/s]{'loss': 4.0844, 'grad_norm': 0.22872169315814972, 'learning_rate': 0.0009759100342119467, 'epoch': 0.19}
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 19%|█▉        | 2025/10696 [43:14<1:11:41,  2.02it/s]
 19%|█▉        | 2026/10696 [43:15<1:11:48,  2.01it/s]
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 19%|█▉        | 2028/10696 [43:16<1:11:50,  2.01it/s]
 19%|█▉        | 2029/10696 [43:16<1:11:43,  2.01it/s]
 19%|█▉        | 2030/10696 [43:17<1:11:43,  2.01it/s]
 19%|█▉        | 2031/10696 [43:17<1:11:35,  2.02it/s]
 19%|█▉        | 2032/10696 [43:18<1:11:34,  2.02it/s]
 19%|█▉        | 2033/10696 [43:18<1:11:31,  2.02it/s]
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 19%|█▉        | 2037/10696 [43:20<1:11:34,  2.02it/s]
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 19%|█▉        | 2039/10696 [43:21<1:11:34,  2.02it/s]
 19%|█▉        | 2040/10696 [43:22<1:11:30,  2.02it/s]
 19%|█▉        | 2041/10696 [43:22<1:11:37,  2.01it/s]
 19%|█▉        | 2042/10696 [43:22<1:11:34,  2.01it/s]
 19%|█▉        | 2043/10696 [43:23<1:11:34,  2.01it/s]
 19%|█▉        | 2044/10696 [43:23<1:11:30,  2.02it/s]
 19%|█▉        | 2045/10696 [43:24<1:11:29,  2.02it/s]
 19%|█▉        | 2046/10696 [43:24<1:11:32,  2.01it/s]
 19%|█▉        | 2047/10696 [43:25<1:11:28,  2.02it/s]
 19%|█▉        | 2048/10696 [43:25<1:11:26,  2.02it/s]
 19%|█▉        | 2049/10696 [43:26<1:11:24,  2.02it/s]
 19%|█▉        | 2050/10696 [43:26<1:11:31,  2.01it/s]{'loss': 4.0706, 'grad_norm': 0.2273617386817932, 'learning_rate': 0.0009746431792338614, 'epoch': 0.19}
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 19%|█▉        | 2050/10696 [43:26<1:11:31,  2.01it/s]
 19%|█▉        | 2051/10696 [43:27<1:11:38,  2.01it/s]
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 19%|█▉        | 2065/10696 [43:34<1:11:22,  2.02it/s]
 19%|█▉        | 2066/10696 [43:34<1:11:24,  2.01it/s]
 19%|█▉        | 2067/10696 [43:35<1:11:22,  2.02it/s]
 19%|█▉        | 2068/10696 [43:35<1:11:22,  2.01it/s]
 19%|█▉        | 2069/10696 [43:36<1:11:25,  2.01it/s]
 19%|█▉        | 2070/10696 [43:36<1:11:28,  2.01it/s]
 19%|█▉        | 2071/10696 [43:37<1:11:24,  2.01it/s]
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 19%|█▉        | 2073/10696 [43:38<1:11:22,  2.01it/s]
 19%|█▉        | 2074/10696 [43:38<1:11:17,  2.02it/s]
 19%|█▉        | 2075/10696 [43:39<1:11:19,  2.01it/s]{'loss': 4.0706, 'grad_norm': 0.23895329236984253, 'learning_rate': 0.000973344726744096, 'epoch': 0.19}
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 19%|█▉        | 2075/10696 [43:39<1:11:19,  2.01it/s]
 19%|█▉        | 2076/10696 [43:39<1:11:23,  2.01it/s]
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 20%|█▉        | 2090/10696 [43:46<1:11:17,  2.01it/s]
 20%|█▉        | 2091/10696 [43:47<1:11:13,  2.01it/s]
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 20%|█▉        | 2093/10696 [43:48<1:11:12,  2.01it/s]
 20%|█▉        | 2094/10696 [43:48<1:11:07,  2.02it/s]
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 20%|█▉        | 2096/10696 [43:49<1:11:07,  2.02it/s]
 20%|█▉        | 2097/10696 [43:50<1:11:07,  2.02it/s]
 20%|█▉        | 2098/10696 [43:50<1:11:06,  2.02it/s]
 20%|█▉        | 2099/10696 [43:51<1:11:05,  2.02it/s]
 20%|█▉        | 2100/10696 [43:51<1:11:08,  2.01it/s]{'loss': 4.0653, 'grad_norm': 0.23844115436077118, 'learning_rate': 0.0009720147631820422, 'epoch': 0.2}
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 20%|█▉        | 2100/10696 [43:51<1:11:08,  2.01it/s]
 20%|█▉        | 2101/10696 [43:52<1:11:08,  2.01it/s]
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{'loss': 4.0448, 'grad_norm': 0.24781110882759094, 'learning_rate': 0.0009663816002944487, 'epoch': 0.21}
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{'loss': 4.0458, 'grad_norm': 0.2479589581489563, 'learning_rate': 0.0009648954511730369, 'epoch': 0.21}
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                                                      {'loss': 4.0247, 'grad_norm': 0.21614372730255127, 'learning_rate': 0.0009553322425018764, 'epoch': 0.22}
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                                                      {'loss': 4.0104, 'grad_norm': 0.24505667388439178, 'learning_rate': 0.0009536316457398286, 'epoch': 0.22}
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                                                      {'loss': 3.9855, 'grad_norm': 0.21237878501415253, 'learning_rate': 0.000938949646507901, 'epoch': 0.24}
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                                                      {'loss': 3.974, 'grad_norm': 0.25204145908355713, 'learning_rate': 0.0009369815761660508, 'epoch': 0.25}
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{'loss': 3.9745, 'grad_norm': 0.24261152744293213, 'learning_rate': 0.0009349844154863192, 'epoch': 0.25}
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{'loss': 3.9595, 'grad_norm': 0.22367818653583527, 'learning_rate': 0.0009245669776607501, 'epoch': 0.26}
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{'loss': 3.9395, 'grad_norm': 0.23608171939849854, 'learning_rate': 0.0009111350768599917, 'epoch': 0.27}
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{'loss': 3.9448, 'grad_norm': 0.21196137368679047, 'learning_rate': 0.0009087997472175057, 'epoch': 0.28}
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{'loss': 3.9106, 'grad_norm': 0.2126377671957016, 'learning_rate': 0.0008865763883171424, 'epoch': 0.3}
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{'loss': 3.8838, 'grad_norm': 0.2106657773256302, 'learning_rate': 0.0008508314109141851, 'epoch': 0.33}
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                                                    {'loss': 3.8701, 'grad_norm': 0.24123533070087433, 'learning_rate': 0.0008299233207584853, 'epoch': 0.34}
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{'loss': 3.868, 'grad_norm': 0.22230562567710876, 'learning_rate': 0.0008237488917283291, 'epoch': 0.35}
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{'loss': 3.8621, 'grad_norm': 0.20217163860797882, 'learning_rate': 0.00081748825487229, 'epoch': 0.35}
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{'loss': 3.8601, 'grad_norm': 0.2352420538663864, 'learning_rate': 0.0008143261285880346, 'epoch': 0.36}
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                                                    {'loss': 3.8505, 'grad_norm': 0.2258002907037735, 'learning_rate': 0.0008047150485213499, 'epoch': 0.36}
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{'loss': 3.8493, 'grad_norm': 0.21331314742565155, 'learning_rate': 0.0007982058802746914, 'epoch': 0.37}
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{'loss': 3.7999, 'grad_norm': 0.22232350707054138, 'learning_rate': 0.0006995649031719709, 'epoch': 0.43}
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{'loss': 3.7891, 'grad_norm': 0.2199602723121643, 'learning_rate': 0.000669236912982712, 'epoch': 0.45}
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{'loss': 3.7866, 'grad_norm': 0.21996110677719116, 'learning_rate': 0.0006537944220299522, 'epoch': 0.46}
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{'loss': 3.7818, 'grad_norm': 0.20157113671302795, 'learning_rate': 0.0006381881325223096, 'epoch': 0.47}
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{'loss': 3.7828, 'grad_norm': 0.23523028194904327, 'learning_rate': 0.0006342629108673174, 'epoch': 0.47}
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                                                      {'loss': 3.7531, 'grad_norm': 0.2090434730052948, 'learning_rate': 0.0005825175439626606, 'epoch': 0.5}
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{'loss': 3.7565, 'grad_norm': 0.1983434110879898, 'learning_rate': 0.0005784912156127941, 'epoch': 0.5}
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                                                      {'loss': 3.7368, 'grad_norm': 0.21931882202625275, 'learning_rate': 0.0005298446772341785, 'epoch': 0.53}
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                                                      {'loss': 3.7382, 'grad_norm': 0.21045862138271332, 'learning_rate': 0.0005216964796855817, 'epoch': 0.54}
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{'loss': 3.7288, 'grad_norm': 0.21949997544288635, 'learning_rate': 0.0004890676327442891, 'epoch': 0.56}
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{'loss': 3.7275, 'grad_norm': 0.21110029518604279, 'learning_rate': 0.00048498945054761957, 'epoch': 0.56}
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{'loss': 3.7307, 'grad_norm': 0.2038554698228836, 'learning_rate': 0.0004809122676195214, 'epoch': 0.56}
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{'loss': 3.7276, 'grad_norm': 0.1997026801109314, 'learning_rate': 0.00047683635538248815, 'epoch': 0.56}
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{'loss': 3.7236, 'grad_norm': 0.21709196269512177, 'learning_rate': 0.00046868942823057036, 'epoch': 0.57}
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{'loss': 3.7167, 'grad_norm': 0.216637521982193, 'learning_rate': 0.00046055083845489774, 'epoch': 0.57}
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{'loss': 3.6978, 'grad_norm': 0.2134978324174881, 'learning_rate': 0.0004200586902273854, 'epoch': 0.6}
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{'loss': 3.7019, 'grad_norm': 0.23082630336284637, 'learning_rate': 0.00038803510214052266, 'epoch': 0.61}
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{'loss': 3.6982, 'grad_norm': 0.21844807267189026, 'learning_rate': 0.00038406290592160846, 'epoch': 0.62}
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{'loss': 3.6923, 'grad_norm': 0.20757026970386505, 'learning_rate': 0.00034869200692616705, 'epoch': 0.64}
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{'loss': 3.6801, 'grad_norm': 0.21871207654476166, 'learning_rate': 0.0003293818606101662, 'epoch': 0.65}
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{'loss': 3.6812, 'grad_norm': 0.20295394957065582, 'learning_rate': 0.0003103556323581765, 'epoch': 0.66}
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{'loss': 3.6666, 'grad_norm': 0.22143453359603882, 'learning_rate': 0.000302831747195701, 'epoch': 0.67}
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{'loss': 3.6542, 'grad_norm': 0.21332766115665436, 'learning_rate': 0.0002482120837512118, 'epoch': 0.7}
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{'loss': 3.659, 'grad_norm': 0.20835785567760468, 'learning_rate': 0.0002446959579842782, 'epoch': 0.7}
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{'loss': 3.6562, 'grad_norm': 0.20994803309440613, 'learning_rate': 0.0002411968280845615, 'epoch': 0.71}
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                                                      {'loss': 3.653, 'grad_norm': 0.23082323372364044, 'learning_rate': 0.00023771492699293744, 'epoch': 0.71}
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{'loss': 3.6609, 'grad_norm': 0.2221626490354538, 'learning_rate': 0.00023425048650334114, 'epoch': 0.71}
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                                                      {'loss': 3.6579, 'grad_norm': 0.21142809092998505, 'learning_rate': 0.00023080373724733688, 'epoch': 0.71}
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{'loss': 3.6522, 'grad_norm': 0.21931134164333344, 'learning_rate': 0.00022737490867876447, 'epoch': 0.72}
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{'loss': 3.6534, 'grad_norm': 0.21333953738212585, 'learning_rate': 0.00022057192543907867, 'epoch': 0.72}
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{'loss': 3.6549, 'grad_norm': 0.22457312047481537, 'learning_rate': 0.0002171982236499444, 'epoch': 0.72}
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{'loss': 3.6452, 'grad_norm': 0.21458929777145386, 'learning_rate': 0.00021384334828205133, 'epoch': 0.72}
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{'loss': 3.6458, 'grad_norm': 0.20776259899139404, 'learning_rate': 0.00021050752267309404, 'epoch': 0.73}
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{'loss': 3.6515, 'grad_norm': 0.21239539980888367, 'learning_rate': 0.00020719096889260485, 'epoch': 0.73}
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                                                      {'loss': 3.6463, 'grad_norm': 0.2098025232553482, 'learning_rate': 0.00020389390772716898, 'epoch': 0.73}
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{'loss': 3.6433, 'grad_norm': 0.21409019827842712, 'learning_rate': 0.0002006165586657271, 'epoch': 0.73}
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{'loss': 3.643, 'grad_norm': 0.20952410995960236, 'learning_rate': 0.00018453308436255068, 'epoch': 0.75}
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{'loss': 3.6351, 'grad_norm': 0.21251598000526428, 'learning_rate': 0.00016290397361663856, 'epoch': 0.76}
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                                                      {'loss': 3.6349, 'grad_norm': 0.21025384962558746, 'learning_rate': 0.0001599022387685824, 'epoch': 0.76}
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{'loss': 3.6367, 'grad_norm': 0.21409523487091064, 'learning_rate': 0.00015396688942545533, 'epoch': 0.77}
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{'loss': 3.6387, 'grad_norm': 0.20665451884269714, 'learning_rate': 0.00015103367005303358, 'epoch': 0.77}
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{'loss': 3.6256, 'grad_norm': 0.21004469692707062, 'learning_rate': 0.00013116234284131755, 'epoch': 0.79}
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{'loss': 3.6291, 'grad_norm': 0.20312950015068054, 'learning_rate': 0.00012842030798157906, 'epoch': 0.79}
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                                                      {'loss': 3.6229, 'grad_norm': 0.21627148985862732, 'learning_rate': 0.00011770133380643444, 'epoch': 0.8}
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{'loss': 3.6309, 'grad_norm': 0.20239612460136414, 'learning_rate': 0.00010738952634273258, 'epoch': 0.81}
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{'loss': 3.6255, 'grad_norm': 0.19748961925506592, 'learning_rate': 9.749586816798511e-05, 'epoch': 0.82}
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{'loss': 3.6266, 'grad_norm': 0.20715846121311188, 'learning_rate': 9.035639087249015e-05, 'epoch': 0.83}
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{'loss': 3.6184, 'grad_norm': 0.20695656538009644, 'learning_rate': 7.900469202587801e-05, 'epoch': 0.84}
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{'loss': 3.6203, 'grad_norm': 0.19646131992340088, 'learning_rate': 7.042686806230747e-05, 'epoch': 0.85}
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{'loss': 3.6136, 'grad_norm': 0.2036823332309723, 'learning_rate': 6.429326379354522e-05, 'epoch': 0.85}
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{'loss': 3.6208, 'grad_norm': 0.20389492809772491, 'learning_rate': 5.8420697172969054e-05, 'epoch': 0.86}
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{'loss': 3.606, 'grad_norm': 0.20445184409618378, 'learning_rate': 5.6521795985227834e-05, 'epoch': 0.86}
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{'loss': 3.6131, 'grad_norm': 0.1995936781167984, 'learning_rate': 5.2812686532640594e-05, 'epoch': 0.87}
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                                                      {'loss': 3.6077, 'grad_norm': 0.2047315090894699, 'learning_rate': 5.100272518723698e-05, 'epoch': 0.87}
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                                                      {'loss': 3.6013, 'grad_norm': 0.20044969022274017, 'learning_rate': 4.575265457427774e-05, 'epoch': 0.88}
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{'loss': 3.6125, 'grad_norm': 0.20624631643295288, 'learning_rate': 4.406295718179226e-05, 'epoch': 0.88}
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{'loss': 3.6178, 'grad_norm': 0.20025713741779327, 'learning_rate': 4.077472953284928e-05, 'epoch': 0.88}
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{'loss': 3.5981, 'grad_norm': 0.20616786181926727, 'learning_rate': 3.760878434778148e-05, 'epoch': 0.89}
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                                                      {'loss': 3.6099, 'grad_norm': 0.20166268944740295, 'learning_rate': 3.309098135390109e-05, 'epoch': 0.9}
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                                                      {'loss': 3.6122, 'grad_norm': 0.197072833776474, 'learning_rate': 3.0234358796002392e-05, 'epoch': 0.9}
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{'loss': 3.6095, 'grad_norm': 0.2004021555185318, 'learning_rate': 2.618419572487507e-05, 'epoch': 0.91}
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{'loss': 3.6146, 'grad_norm': 0.20714204013347626, 'learning_rate': 2.4897108491227004e-05, 'epoch': 0.91}
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{'loss': 3.6116, 'grad_norm': 0.1958046555519104, 'learning_rate': 2.1225947679658798e-05, 'epoch': 0.92}
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{'loss': 3.6024, 'grad_norm': 0.1982419490814209, 'learning_rate': 2.0065865920819825e-05, 'epoch': 0.92}
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{'loss': 3.6127, 'grad_norm': 0.1987472027540207, 'learning_rate': 1.4746173182482558e-05, 'epoch': 0.93}
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                                                       {'loss': 3.611, 'grad_norm': 0.1951916515827179, 'learning_rate': 9.429112362712766e-06, 'epoch': 0.94}
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{'loss': 3.6088, 'grad_norm': 0.19970227777957916, 'learning_rate': 8.65691278778591e-06, 'epoch': 0.95}
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{'loss': 3.6002, 'grad_norm': 0.19450533390045166, 'learning_rate': 7.210690594653957e-06, 'epoch': 0.95}
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{'loss': 3.601, 'grad_norm': 0.19620297849178314, 'learning_rate': 1.0226148330599872e-06, 'epoch': 0.98}
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{'loss': 3.6022, 'grad_norm': 0.19827377796173096, 'learning_rate': 7.784442886591414e-07, 'epoch': 0.98}
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{'loss': 3.6045, 'grad_norm': 0.19849486649036407, 'learning_rate': 2.453889365874873e-07, 'epoch': 0.99}
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{'loss': 3.6001, 'grad_norm': 0.19333095848560333, 'learning_rate': 1.34228675331749e-07, 'epoch': 0.99}
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100%|█████████▉| 10650/10696 [1:54:41<00:22,  2.01it/s]{'loss': 3.6011, 'grad_norm': 0.19635756313800812, 'learning_rate': 5.634502109158612e-08, 'epoch': 1.0}
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100%|█████████▉| 10675/10696 [1:54:54<00:10,  2.01it/s]{'loss': 3.604, 'grad_norm': 0.19714075326919556, 'learning_rate': 1.1743158666366327e-08, 'epoch': 1.0}
                                                       
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{'train_runtime': 6917.2103, 'train_samples_per_second': 1583.429, 'train_steps_per_second': 1.546, 'train_loss': 3.9810526098167176, 'epoch': 1.0}
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{'loss': 9.1946, 'grad_norm': 1.232470989227295, 'learning_rate': 6.996268656716417e-05, 'epoch': 0.01}
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{'loss': 7.8219, 'grad_norm': 0.4748566448688507, 'learning_rate': 0.00011660447761194031, 'epoch': 0.01}
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{'loss': 7.3884, 'grad_norm': 0.3904429078102112, 'learning_rate': 0.00013992537313432834, 'epoch': 0.01}
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{'loss': 7.0429, 'grad_norm': 0.36491721868515015, 'learning_rate': 0.00016324626865671642, 'epoch': 0.02}
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{'loss': 6.7755, 'grad_norm': 0.36932021379470825, 'learning_rate': 0.00018656716417910448, 'epoch': 0.02}
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{'loss': 6.5533, 'grad_norm': 0.4625686705112457, 'learning_rate': 0.00020988805970149256, 'epoch': 0.02}
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{'loss': 6.3652, 'grad_norm': 0.6517781615257263, 'learning_rate': 0.00023320895522388062, 'epoch': 0.02}
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{'loss': 6.2057, 'grad_norm': 0.521963357925415, 'learning_rate': 0.00025652985074626865, 'epoch': 0.03}
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{'loss': 6.0639, 'grad_norm': 0.6356621384620667, 'learning_rate': 0.0002798507462686567, 'epoch': 0.03}
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{'loss': 5.9374, 'grad_norm': 0.9694742560386658, 'learning_rate': 0.00030317164179104476, 'epoch': 0.03}
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{'loss': 5.8363, 'grad_norm': 0.6399821043014526, 'learning_rate': 0.00032649253731343285, 'epoch': 0.03}
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{'loss': 5.7355, 'grad_norm': 0.6212801933288574, 'learning_rate': 0.0003498134328358209, 'epoch': 0.04}
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{'loss': 5.6503, 'grad_norm': 0.6092248558998108, 'learning_rate': 0.00037313432835820896, 'epoch': 0.04}
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{'loss': 5.5606, 'grad_norm': 0.5750597715377808, 'learning_rate': 0.00039645522388059704, 'epoch': 0.04}
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{'loss': 5.4866, 'grad_norm': 0.6031320095062256, 'learning_rate': 0.0004197761194029851, 'epoch': 0.04}
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{'loss': 5.426, 'grad_norm': 0.5352821350097656, 'learning_rate': 0.00044309701492537316, 'epoch': 0.04}
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{'loss': 5.3474, 'grad_norm': 0.582328736782074, 'learning_rate': 0.00046641791044776124, 'epoch': 0.05}
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{'loss': 5.2846, 'grad_norm': 0.7820909023284912, 'learning_rate': 0.0004897388059701492, 'epoch': 0.05}
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{'loss': 5.2276, 'grad_norm': 0.4914645552635193, 'learning_rate': 0.0005130597014925373, 'epoch': 0.05}
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{'loss': 5.1826, 'grad_norm': 0.5939364433288574, 'learning_rate': 0.0005363805970149254, 'epoch': 0.05}
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{'loss': 5.127, 'grad_norm': 0.5419163107872009, 'learning_rate': 0.0005597014925373134, 'epoch': 0.06}
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{'loss': 5.0888, 'grad_norm': 0.4555201828479767, 'learning_rate': 0.0005830223880597015, 'epoch': 0.06}
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{'loss': 5.0436, 'grad_norm': 0.521930992603302, 'learning_rate': 0.0006063432835820895, 'epoch': 0.06}
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{'loss': 4.9987, 'grad_norm': 0.5239168405532837, 'learning_rate': 0.0006296641791044776, 'epoch': 0.06}
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{'loss': 4.9646, 'grad_norm': 0.42984968423843384, 'learning_rate': 0.0006529850746268657, 'epoch': 0.07}
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{'loss': 4.9297, 'grad_norm': 0.484243243932724, 'learning_rate': 0.0006763059701492538, 'epoch': 0.07}
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{'loss': 4.8905, 'grad_norm': 0.40631452202796936, 'learning_rate': 0.0006996268656716418, 'epoch': 0.07}
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{'loss': 4.8599, 'grad_norm': 0.46862027049064636, 'learning_rate': 0.0007229477611940298, 'epoch': 0.07}
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{'loss': 4.8285, 'grad_norm': 0.5541700720787048, 'learning_rate': 0.0007462686567164179, 'epoch': 0.07}
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{'loss': 4.799, 'grad_norm': 0.4129628837108612, 'learning_rate': 0.000769589552238806, 'epoch': 0.08}
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{'loss': 4.7757, 'grad_norm': 0.37515711784362793, 'learning_rate': 0.0007929104477611941, 'epoch': 0.08}
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{'loss': 4.7367, 'grad_norm': 0.4243326783180237, 'learning_rate': 0.0008162313432835821, 'epoch': 0.08}
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{'loss': 4.7162, 'grad_norm': 0.35857799649238586, 'learning_rate': 0.0008395522388059703, 'epoch': 0.08}
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{'loss': 4.6957, 'grad_norm': 0.39365464448928833, 'learning_rate': 0.0008628731343283582, 'epoch': 0.09}
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{'loss': 4.6594, 'grad_norm': 0.4399496614933014, 'learning_rate': 0.0008861940298507463, 'epoch': 0.09}
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{'loss': 4.6502, 'grad_norm': 0.34628477692604065, 'learning_rate': 0.0009095149253731343, 'epoch': 0.09}
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{'loss': 4.6188, 'grad_norm': 0.4109642207622528, 'learning_rate': 0.0009328358208955225, 'epoch': 0.09}
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{'loss': 4.5874, 'grad_norm': 0.3740506172180176, 'learning_rate': 0.0009561567164179105, 'epoch': 0.1}
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{'loss': 4.574, 'grad_norm': 0.3145410120487213, 'learning_rate': 0.0009794776119402984, 'epoch': 0.1}
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{'loss': 4.55, 'grad_norm': 0.3126870393753052, 'learning_rate': 0.0009999997610383759, 'epoch': 0.1}
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{'loss': 4.5359, 'grad_norm': 0.30544576048851013, 'learning_rate': 0.0009999791839302003, 'epoch': 0.1}
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{'loss': 4.5109, 'grad_norm': 0.34079593420028687, 'learning_rate': 0.0009999254192702488, 'epoch': 0.11}
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{'loss': 4.5008, 'grad_norm': 0.30385568737983704, 'learning_rate': 0.0009998384706273048, 'epoch': 0.11}
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{'loss': 4.4789, 'grad_norm': 0.30299264192581177, 'learning_rate': 0.000999718343772834, 'epoch': 0.11}
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{'loss': 4.4534, 'grad_norm': 0.30539777874946594, 'learning_rate': 0.0009995650466806004, 'epoch': 0.11}
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{'loss': 4.4415, 'grad_norm': 0.3044697046279907, 'learning_rate': 0.0009993785895261384, 'epoch': 0.11}
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{'loss': 4.4289, 'grad_norm': 0.31845763325691223, 'learning_rate': 0.000999158984686076, 'epoch': 0.12}
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{'loss': 4.4053, 'grad_norm': 0.2737877666950226, 'learning_rate': 0.000998906246737314, 'epoch': 0.12}
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{'loss': 4.4012, 'grad_norm': 0.2995099425315857, 'learning_rate': 0.0009986203924560587, 'epoch': 0.12}
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{'loss': 4.39, 'grad_norm': 0.3088318407535553, 'learning_rate': 0.0009983014408167072, 'epoch': 0.12}
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{'loss': 4.3715, 'grad_norm': 0.28549715876579285, 'learning_rate': 0.0009979494129905891, 'epoch': 0.13}
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{'loss': 4.3583, 'grad_norm': 0.25411444902420044, 'learning_rate': 0.0009975643323445608, 'epoch': 0.13}
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{'loss': 4.3563, 'grad_norm': 0.2650745213031769, 'learning_rate': 0.0009971462244394538, 'epoch': 0.13}
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{'loss': 4.3328, 'grad_norm': 0.2654881477355957, 'learning_rate': 0.0009966951170283793, 'epoch': 0.13}
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{'loss': 4.3309, 'grad_norm': 0.29075887799263, 'learning_rate': 0.000996211040054885, 'epoch': 0.14}
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{'loss': 4.3112, 'grad_norm': 0.24770638346672058, 'learning_rate': 0.0009956940256509682, 'epoch': 0.14}
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{'loss': 4.3045, 'grad_norm': 0.24644799530506134, 'learning_rate': 0.0009951441081349414, 'epoch': 0.14}
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{'loss': 4.2978, 'grad_norm': 0.26171353459358215, 'learning_rate': 0.0009945613240091573, 'epoch': 0.14}
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{'loss': 4.2824, 'grad_norm': 0.25666242837905884, 'learning_rate': 0.0009939457119575823, 'epoch': 0.14}
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{'loss': 4.2776, 'grad_norm': 0.2592921555042267, 'learning_rate': 0.000993297312843232, 'epoch': 0.15}
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{'loss': 4.2663, 'grad_norm': 0.2505224347114563, 'learning_rate': 0.0009926161697054558, 'epoch': 0.15}
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{'loss': 4.2583, 'grad_norm': 0.2425021529197693, 'learning_rate': 0.000991902327757083, 'epoch': 0.15}
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{'loss': 4.2497, 'grad_norm': 0.2643587291240692, 'learning_rate': 0.000991155834381419, 'epoch': 0.15}
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{'loss': 4.2508, 'grad_norm': 0.24532604217529297, 'learning_rate': 0.0009903767391291024, 'epoch': 0.16}
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{'loss': 4.2363, 'grad_norm': 0.25432372093200684, 'learning_rate': 0.0009895650937148137, 'epoch': 0.16}
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{'loss': 4.2263, 'grad_norm': 0.23738078773021698, 'learning_rate': 0.0009887209520138443, 'epoch': 0.16}
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{'loss': 4.227, 'grad_norm': 0.2520458698272705, 'learning_rate': 0.0009878443700585202, 'epoch': 0.16}
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{'loss': 4.2151, 'grad_norm': 0.22984232008457184, 'learning_rate': 0.0009869354060344812, 'epoch': 0.17}
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{'loss': 4.2111, 'grad_norm': 0.24741072952747345, 'learning_rate': 0.000985994120276821, 'epoch': 0.17}
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{'loss': 4.2049, 'grad_norm': 0.2311837077140808, 'learning_rate': 0.0009850205752660803, 'epoch': 0.17}
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{'loss': 4.1946, 'grad_norm': 0.23028145730495453, 'learning_rate': 0.0009840148356241001, 'epoch': 0.17}
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{'loss': 4.1866, 'grad_norm': 0.2419293373823166, 'learning_rate': 0.0009829769681097328, 'epoch': 0.18}
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{'loss': 4.1844, 'grad_norm': 0.23229561746120453, 'learning_rate': 0.00098190704161441, 'epoch': 0.18}
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{'loss': 4.176, 'grad_norm': 0.2197273224592209, 'learning_rate': 0.0009808051271575705, 'epoch': 0.18}
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{'loss': 4.1689, 'grad_norm': 0.23823750019073486, 'learning_rate': 0.0009796712978819458, 'epoch': 0.18}
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{'loss': 4.1711, 'grad_norm': 0.24251116812229156, 'learning_rate': 0.0009785056290487041, 'epoch': 0.18}
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{'loss': 4.1565, 'grad_norm': 0.231139674782753, 'learning_rate': 0.000977308198032457, 'epoch': 0.19}
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{'loss': 4.1544, 'grad_norm': 0.24080336093902588, 'learning_rate': 0.0009760790843161207, 'epoch': 0.19}
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{'loss': 4.1398, 'grad_norm': 0.23006339371204376, 'learning_rate': 0.0009748183694856421, 'epoch': 0.19}
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{'loss': 4.1476, 'grad_norm': 0.2322188764810562, 'learning_rate': 0.0009735261372245824, 'epoch': 0.19}
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{'loss': 4.1436, 'grad_norm': 0.22273346781730652, 'learning_rate': 0.0009722024733085633, 'epoch': 0.2}
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{'loss': 4.1237, 'grad_norm': 0.236967995762825, 'learning_rate': 0.0009708474655995716, 'epoch': 0.2}
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{'loss': 4.1329, 'grad_norm': 0.22125343978405, 'learning_rate': 0.0009694612040401292, 'epoch': 0.2}
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{'loss': 4.1174, 'grad_norm': 0.23412485420703888, 'learning_rate': 0.0009680437806473211, 'epoch': 0.2}
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{'loss': 4.1208, 'grad_norm': 0.24572426080703735, 'learning_rate': 0.0009665952895066891, 'epoch': 0.21}
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{'loss': 4.1182, 'grad_norm': 0.22761030495166779, 'learning_rate': 0.0009651158267659854, 'epoch': 0.21}
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{'loss': 4.1062, 'grad_norm': 0.2252587080001831, 'learning_rate': 0.0009636054906287911, 'epoch': 0.21}
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{'loss': 4.1046, 'grad_norm': 0.22365300357341766, 'learning_rate': 0.0009620643813479973, 'epoch': 0.21}
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{'loss': 4.0922, 'grad_norm': 0.22491547465324402, 'learning_rate': 0.000960492601219151, 'epoch': 0.21}
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{'loss': 4.1002, 'grad_norm': 0.2159612476825714, 'learning_rate': 0.0009588902545736645, 'epoch': 0.22}
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{'loss': 4.0943, 'grad_norm': 0.2216760814189911, 'learning_rate': 0.0009572574477718903, 'epoch': 0.22}
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{'loss': 4.0904, 'grad_norm': 0.24070511758327484, 'learning_rate': 0.0009555942891960611, 'epoch': 0.22}
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{'loss': 4.0935, 'grad_norm': 0.23899497091770172, 'learning_rate': 0.000953900889243096, 'epoch': 0.22}
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{'loss': 4.0859, 'grad_norm': 0.2153318077325821, 'learning_rate': 0.0009521773603172715, 'epoch': 0.23}
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{'loss': 4.0803, 'grad_norm': 0.21983036398887634, 'learning_rate': 0.0009504238168227613, 'epoch': 0.23}
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{'loss': 4.0776, 'grad_norm': 0.22949561476707458, 'learning_rate': 0.0009486403751560427, 'epoch': 0.23}
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{'loss': 4.0713, 'grad_norm': 0.21205829083919525, 'learning_rate': 0.000946827153698169, 'epoch': 0.23}
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{'loss': 4.0674, 'grad_norm': 0.23921458423137665, 'learning_rate': 0.0009449842728069133, 'epoch': 0.24}
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{'loss': 4.0686, 'grad_norm': 0.2394738346338272, 'learning_rate': 0.0009431118548087783, 'epoch': 0.24}
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{'loss': 4.0643, 'grad_norm': 0.20525667071342468, 'learning_rate': 0.0009412100239908767, 'epoch': 0.24}
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{'loss': 4.0532, 'grad_norm': 0.21949905157089233, 'learning_rate': 0.0009392789065926817, 'epoch': 0.24}
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{'loss': 4.0525, 'grad_norm': 0.22180511057376862, 'learning_rate': 0.000937318630797647, 'epoch': 0.25}
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{'loss': 4.0504, 'grad_norm': 0.22880275547504425, 'learning_rate': 0.0009353293267246988, 'epoch': 0.25}
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{'loss': 4.0476, 'grad_norm': 0.21763809025287628, 'learning_rate': 0.0009333111264195981, 'epoch': 0.25}
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{'loss': 4.0486, 'grad_norm': 0.22851434350013733, 'learning_rate': 0.0009312641638461767, 'epoch': 0.25}
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{'loss': 4.0435, 'grad_norm': 0.22952334582805634, 'learning_rate': 0.0009291885748774436, 'epoch': 0.25}
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{'loss': 4.033, 'grad_norm': 0.23193401098251343, 'learning_rate': 0.0009270844972865675, 'epoch': 0.26}
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{'loss': 4.0334, 'grad_norm': 0.21900106966495514, 'learning_rate': 0.0009249520707377309, 'epoch': 0.26}
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{'loss': 4.0336, 'grad_norm': 0.22678866982460022, 'learning_rate': 0.0009227914367768598, 'epoch': 0.26}
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{'loss': 4.0352, 'grad_norm': 0.2122090756893158, 'learning_rate': 0.0009206027388222276, 'epoch': 0.26}
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{'loss': 4.0265, 'grad_norm': 0.221161887049675, 'learning_rate': 0.0009183861221549363, 'epoch': 0.27}
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{'loss': 4.0239, 'grad_norm': 0.2102159857749939, 'learning_rate': 0.0009161417339092721, 'epoch': 0.27}
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{'loss': 4.012, 'grad_norm': 0.21164174377918243, 'learning_rate': 0.0009138697230629397, 'epoch': 0.27}
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{'loss': 4.0148, 'grad_norm': 0.2197403460741043, 'learning_rate': 0.0009115702404271726, 'epoch': 0.27}
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{'loss': 4.0125, 'grad_norm': 0.22883053123950958, 'learning_rate': 0.0009092434386367234, 'epoch': 0.28}
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{'loss': 4.0127, 'grad_norm': 0.2082654982805252, 'learning_rate': 0.0009068894721397322, 'epoch': 0.28}
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{'loss': 4.0051, 'grad_norm': 0.20694366097450256, 'learning_rate': 0.0009021006718239868, 'epoch': 0.28}
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{'loss': 3.9962, 'grad_norm': 0.22039678692817688, 'learning_rate': 0.0008996661558755833, 'epoch': 0.28}
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{'loss': 3.9934, 'grad_norm': 0.21867643296718597, 'learning_rate': 0.000897205110940239, 'epoch': 0.29}
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{'loss': 3.9913, 'grad_norm': 0.20916356146335602, 'learning_rate': 0.0008947177003768671, 'epoch': 0.29}
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{'loss': 3.9949, 'grad_norm': 0.22793959081172943, 'learning_rate': 0.0008922040892944755, 'epoch': 0.29}
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{'loss': 3.9855, 'grad_norm': 0.20497047901153564, 'learning_rate': 0.0008896644445412061, 'epoch': 0.29}
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{'loss': 3.9871, 'grad_norm': 0.22478143870830536, 'learning_rate': 0.0008870989346932607, 'epoch': 0.3}
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{'loss': 3.9887, 'grad_norm': 0.22492775321006775, 'learning_rate': 0.0008845077300437107, 'epoch': 0.3}
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{'loss': 3.9845, 'grad_norm': 0.20808009803295135, 'learning_rate': 0.0008818910025911937, 'epoch': 0.3}
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{'loss': 3.9818, 'grad_norm': 0.2027365118265152, 'learning_rate': 0.0008792489260284965, 'epoch': 0.3}
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{'loss': 3.9725, 'grad_norm': 0.20646992325782776, 'learning_rate': 0.0008765816757310259, 'epoch': 0.31}
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{'loss': 3.9797, 'grad_norm': 0.23129908740520477, 'learning_rate': 0.0008738894287451674, 'epoch': 0.31}
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{'loss': 3.9708, 'grad_norm': 0.20462816953659058, 'learning_rate': 0.0008711723637765334, 'epoch': 0.31}
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{'loss': 3.973, 'grad_norm': 0.21348722279071808, 'learning_rate': 0.0008684306611781009, 'epoch': 0.31}
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{'loss': 3.974, 'grad_norm': 0.21654319763183594, 'learning_rate': 0.0008656645029382404, 'epoch': 0.32}
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{'loss': 3.969, 'grad_norm': 0.24296072125434875, 'learning_rate': 0.0008628740726686357, 'epoch': 0.32}
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{'loss': 3.9651, 'grad_norm': 0.2045918107032776, 'learning_rate': 0.000860059555592096, 'epoch': 0.32}
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{'loss': 3.9612, 'grad_norm': 0.2068096250295639, 'learning_rate': 0.0008572211385302617, 'epoch': 0.32}
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{'loss': 3.9625, 'grad_norm': 0.21065793931484222, 'learning_rate': 0.0008543590098912028, 'epoch': 0.32}
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{'loss': 3.9633, 'grad_norm': 0.21324597299098969, 'learning_rate': 0.0008514733596569138, 'epoch': 0.33}
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{'loss': 3.9529, 'grad_norm': 0.22072970867156982, 'learning_rate': 0.0008485643793707016, 'epoch': 0.33}
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{'loss': 3.948, 'grad_norm': 0.20108561217784882, 'learning_rate': 0.0008456322621244734, 'epoch': 0.33}
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{'loss': 3.9502, 'grad_norm': 0.21259693801403046, 'learning_rate': 0.0008426772025459173, 'epoch': 0.33}
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{'loss': 3.9481, 'grad_norm': 0.20228517055511475, 'learning_rate': 0.0008396993967855852, 'epoch': 0.34}
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{'loss': 3.9454, 'grad_norm': 0.21809101104736328, 'learning_rate': 0.000836699042503872, 'epoch': 0.34}
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{'loss': 3.9365, 'grad_norm': 0.2014588713645935, 'learning_rate': 0.0008306314864882747, 'epoch': 0.34}
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{'loss': 3.9473, 'grad_norm': 0.21547779440879822, 'learning_rate': 0.0008275646875058169, 'epoch': 0.35}
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{'loss': 3.9402, 'grad_norm': 0.21840572357177734, 'learning_rate': 0.0008244761454780962, 'epoch': 0.35}
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{'loss': 3.9434, 'grad_norm': 0.21011513471603394, 'learning_rate': 0.0008213660654159454, 'epoch': 0.35}
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{'loss': 3.9385, 'grad_norm': 0.21535202860832214, 'learning_rate': 0.0008182346537598444, 'epoch': 0.35}
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{'loss': 3.9341, 'grad_norm': 0.2287270724773407, 'learning_rate': 0.0008150821183662201, 'epoch': 0.35}
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{'loss': 3.9312, 'grad_norm': 0.2248304784297943, 'learning_rate': 0.0008119086684936474, 'epoch': 0.36}
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{'loss': 3.932, 'grad_norm': 0.20805129408836365, 'learning_rate': 0.00080871451478896, 'epoch': 0.36}
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{'loss': 3.9186, 'grad_norm': 0.22739370167255402, 'learning_rate': 0.0008054998692732676, 'epoch': 0.36}
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{'loss': 3.9251, 'grad_norm': 0.20691752433776855, 'learning_rate': 0.0008022649453278827, 'epoch': 0.36}
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{'loss': 3.9261, 'grad_norm': 0.2151794731616974, 'learning_rate': 0.0007990099576801568, 'epoch': 0.37}
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{'loss': 3.9225, 'grad_norm': 0.22644701600074768, 'learning_rate': 0.0007957351223892271, 'epoch': 0.37}
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{'loss': 3.9239, 'grad_norm': 0.21284539997577667, 'learning_rate': 0.0007924406568316749, 'epoch': 0.37}
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{'loss': 3.9222, 'grad_norm': 0.20855498313903809, 'learning_rate': 0.0007891267796870969, 'epoch': 0.37}
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{'loss': 3.9196, 'grad_norm': 0.24686047434806824, 'learning_rate': 0.0007857937109235893, 'epoch': 0.38}
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{'loss': 3.9155, 'grad_norm': 0.2394084334373474, 'learning_rate': 0.0007824416717831475, 'epoch': 0.38}
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{'loss': 3.9109, 'grad_norm': 0.21282514929771423, 'learning_rate': 0.0007790708847669796, 'epoch': 0.38}
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{'loss': 3.91, 'grad_norm': 0.21939793229103088, 'learning_rate': 0.0007756815736207379, 'epoch': 0.38}
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{'loss': 3.9054, 'grad_norm': 0.20735333859920502, 'learning_rate': 0.000772273963319667, 'epoch': 0.39}
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{'loss': 3.9001, 'grad_norm': 0.2054857313632965, 'learning_rate': 0.0007688482800536699, 'epoch': 0.39}
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{'loss': 3.9049, 'grad_norm': 0.22095957398414612, 'learning_rate': 0.000765404751212295, 'epoch': 0.39}
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{'loss': 3.9073, 'grad_norm': 0.2129284292459488, 'learning_rate': 0.0007619436053696421, 'epoch': 0.39}
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{'loss': 3.8962, 'grad_norm': 0.20480123162269592, 'learning_rate': 0.0007584650722691891, 'epoch': 0.39}
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{'loss': 3.8935, 'grad_norm': 0.20969925820827484, 'learning_rate': 0.0007549693828085437, 'epoch': 0.4}
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{'loss': 3.9013, 'grad_norm': 0.20632144808769226, 'learning_rate': 0.0007514567690241163, 'epoch': 0.4}
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{'loss': 3.8877, 'grad_norm': 0.2103457748889923, 'learning_rate': 0.0007443817022310808, 'epoch': 0.4}
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{'loss': 3.892, 'grad_norm': 0.2115333378314972, 'learning_rate': 0.0007408197188503156, 'epoch': 0.41}
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{'loss': 3.8892, 'grad_norm': 0.21711914241313934, 'learning_rate': 0.0007372417503702805, 'epoch': 0.41}
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{'loss': 3.8854, 'grad_norm': 0.20337072014808655, 'learning_rate': 0.0007336480342888914, 'epoch': 0.41}
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{'loss': 3.879, 'grad_norm': 0.21024949848651886, 'learning_rate': 0.0007300388091493566, 'epoch': 0.41}
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{'loss': 3.889, 'grad_norm': 0.22498299181461334, 'learning_rate': 0.0007264143145243422, 'epoch': 0.42}
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{'loss': 3.8776, 'grad_norm': 0.21598780155181885, 'learning_rate': 0.0007227747910000704, 'epoch': 0.42}
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{'loss': 3.876, 'grad_norm': 0.2106993943452835, 'learning_rate': 0.0007191204801603497, 'epoch': 0.42}
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{'loss': 3.8711, 'grad_norm': 0.22296272218227386, 'learning_rate': 0.000715451624570539, 'epoch': 0.42}
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{'loss': 3.8772, 'grad_norm': 0.2102101594209671, 'learning_rate': 0.0007117684677614468, 'epoch': 0.42}
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{'loss': 3.8779, 'grad_norm': 0.21556006371974945, 'learning_rate': 0.0007080712542131656, 'epoch': 0.43}
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{'loss': 3.872, 'grad_norm': 0.2141294926404953, 'learning_rate': 0.000704360229338845, 'epoch': 0.43}
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{'loss': 3.8689, 'grad_norm': 0.2034437209367752, 'learning_rate': 0.0007006356394684002, 'epoch': 0.43}
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{'loss': 3.8761, 'grad_norm': 0.219057098031044, 'learning_rate': 0.0006968977318321625, 'epoch': 0.43}
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{'loss': 3.8611, 'grad_norm': 0.1960822343826294, 'learning_rate': 0.000693146754544468, 'epoch': 0.44}
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{'loss': 3.8659, 'grad_norm': 0.20461201667785645, 'learning_rate': 0.0006893829565871878, 'epoch': 0.44}
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{'loss': 3.865, 'grad_norm': 0.21092836558818817, 'learning_rate': 0.0006856065877932025, 'epoch': 0.44}
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{'loss': 3.8661, 'grad_norm': 0.22660763561725616, 'learning_rate': 0.0006818178988298176, 'epoch': 0.44}
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{'loss': 3.8626, 'grad_norm': 0.21123173832893372, 'learning_rate': 0.000678017141182125, 'epoch': 0.45}
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{'loss': 3.8614, 'grad_norm': 0.20315948128700256, 'learning_rate': 0.0006742045671363106, 'epoch': 0.45}
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{'loss': 3.8619, 'grad_norm': 0.20469607412815094, 'learning_rate': 0.0006703804297629074, 'epoch': 0.45}
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{'loss': 3.858, 'grad_norm': 0.2119603455066681, 'learning_rate': 0.0006665449828999971, 'epoch': 0.45}
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{'loss': 3.8568, 'grad_norm': 0.20451584458351135, 'learning_rate': 0.0006626984811363616, 'epoch': 0.46}
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{'loss': 3.8575, 'grad_norm': 0.20463266968727112, 'learning_rate': 0.0006588411797945836, 'epoch': 0.46}
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{'loss': 3.8472, 'grad_norm': 0.2138034999370575, 'learning_rate': 0.0006549733349140982, 'epoch': 0.46}
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{'loss': 3.8502, 'grad_norm': 0.21833238005638123, 'learning_rate': 0.0006510952032341988, 'epoch': 0.46}
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{'loss': 3.8464, 'grad_norm': 0.21125322580337524, 'learning_rate': 0.000647207042176994, 'epoch': 0.46}
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{'loss': 3.853, 'grad_norm': 0.20933189988136292, 'learning_rate': 0.0006433091098303216, 'epoch': 0.47}
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{'loss': 3.8444, 'grad_norm': 0.21680133044719696, 'learning_rate': 0.0006394016649306164, 'epoch': 0.47}
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{'loss': 3.8452, 'grad_norm': 0.2101084291934967, 'learning_rate': 0.0006354849668457362, 'epoch': 0.47}
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{'loss': 3.8442, 'grad_norm': 0.2246551811695099, 'learning_rate': 0.0006315592755577455, 'epoch': 0.47}
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{'loss': 3.8416, 'grad_norm': 0.20728498697280884, 'learning_rate': 0.0006276248516456589, 'epoch': 0.48}
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{'loss': 3.8465, 'grad_norm': 0.22376541793346405, 'learning_rate': 0.0006236819562681432, 'epoch': 0.48}
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{'loss': 3.8417, 'grad_norm': 0.20333391427993774, 'learning_rate': 0.0006197308511461836, 'epoch': 0.48}
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{'loss': 3.8356, 'grad_norm': 0.20645564794540405, 'learning_rate': 0.0006157717985457101, 'epoch': 0.48}
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{'loss': 3.8449, 'grad_norm': 0.20761875808238983, 'learning_rate': 0.00061180506126019, 'epoch': 0.49}
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{'loss': 3.8369, 'grad_norm': 0.2203957885503769, 'learning_rate': 0.0006078309025931831, 'epoch': 0.49}
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{'loss': 3.8352, 'grad_norm': 0.2095993012189865, 'learning_rate': 0.0006038495863408649, 'epoch': 0.49}
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{'loss': 3.83, 'grad_norm': 0.19913402199745178, 'learning_rate': 0.0005998613767745162, 'epoch': 0.49}
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{'loss': 3.8412, 'grad_norm': 0.21788804233074188, 'learning_rate': 0.0005958665386229811, 'epoch': 0.49}
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{'loss': 3.8296, 'grad_norm': 0.23261277377605438, 'learning_rate': 0.0005918653370550951, 'epoch': 0.5}
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{'loss': 3.8215, 'grad_norm': 0.2175263911485672, 'learning_rate': 0.0005717731874589576, 'epoch': 0.51}
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{'loss': 3.8256, 'grad_norm': 0.21246854960918427, 'learning_rate': 0.0005677393963568244, 'epoch': 0.51}
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{'loss': 3.8176, 'grad_norm': 0.21241505444049835, 'learning_rate': 0.0005637011088580488, 'epoch': 0.51}
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{'loss': 3.8251, 'grad_norm': 0.20916153490543365, 'learning_rate': 0.0005596585930155414, 'epoch': 0.52}
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{'loss': 3.8133, 'grad_norm': 0.2094469517469406, 'learning_rate': 0.0005556121171628811, 'epoch': 0.52}
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{'loss': 3.8167, 'grad_norm': 0.21600766479969025, 'learning_rate': 0.000551561949896504, 'epoch': 0.52}
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{'loss': 3.8188, 'grad_norm': 0.2076546549797058, 'learning_rate': 0.0005475083600578742, 'epoch': 0.52}
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{'loss': 3.8132, 'grad_norm': 0.20434843003749847, 'learning_rate': 0.0005434516167156389, 'epoch': 0.53}
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{'loss': 3.8132, 'grad_norm': 0.2072751820087433, 'learning_rate': 0.0005393919891477681, 'epoch': 0.53}
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{'loss': 3.8213, 'grad_norm': 0.20008933544158936, 'learning_rate': 0.0005353297468236806, 'epoch': 0.53}
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{'loss': 3.8083, 'grad_norm': 0.20227479934692383, 'learning_rate': 0.0005312651593863571, 'epoch': 0.53}
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{'loss': 3.8099, 'grad_norm': 0.21218886971473694, 'learning_rate': 0.0005271984966344421, 'epoch': 0.53}
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{'loss': 3.8059, 'grad_norm': 0.22931993007659912, 'learning_rate': 0.0005231300285043346, 'epoch': 0.54}
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{'loss': 3.8045, 'grad_norm': 0.2048569917678833, 'learning_rate': 0.0005149887564364004, 'epoch': 0.54}
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{'loss': 3.7935, 'grad_norm': 0.20744208991527557, 'learning_rate': 0.0005109164928988476, 'epoch': 0.54}
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{'loss': 3.8042, 'grad_norm': 0.21113325655460358, 'learning_rate': 0.0005068435047477813, 'epoch': 0.55}
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{'loss': 3.8051, 'grad_norm': 0.21107624471187592, 'learning_rate': 0.000502770062339467, 'epoch': 0.55}
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{'loss': 3.798, 'grad_norm': 0.20833522081375122, 'learning_rate': 0.0004986964360603231, 'epoch': 0.55}
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{'loss': 3.7982, 'grad_norm': 0.21108438074588776, 'learning_rate': 0.000494622896308973, 'epoch': 0.55}
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{'loss': 3.7978, 'grad_norm': 0.19907768070697784, 'learning_rate': 0.0004905497134782966, 'epoch': 0.56}
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{'loss': 3.7919, 'grad_norm': 0.20812588930130005, 'learning_rate': 0.00048647715793748213, 'epoch': 0.56}
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{'loss': 3.7936, 'grad_norm': 0.22058948874473572, 'learning_rate': 0.00048240550001407955, 'epoch': 0.56}
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{'loss': 3.7908, 'grad_norm': 0.20529143512248993, 'learning_rate': 0.00047833500997605707, 'epoch': 0.56}
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{'loss': 3.7909, 'grad_norm': 0.19835951924324036, 'learning_rate': 0.0004742659580138609, 'epoch': 0.56}
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{'loss': 3.7882, 'grad_norm': 0.20252130925655365, 'learning_rate': 0.0004701986142224813, 'epoch': 0.57}
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{'loss': 3.7861, 'grad_norm': 0.20584744215011597, 'learning_rate': 0.0004661332485835234, 'epoch': 0.57}
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{'loss': 3.7878, 'grad_norm': 0.21216273307800293, 'learning_rate': 0.0004620701309472869, 'epoch': 0.57}
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{'loss': 3.7877, 'grad_norm': 0.2097010612487793, 'learning_rate': 0.0004580095310148539, 'epoch': 0.57}
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{'loss': 3.7776, 'grad_norm': 0.2103867083787918, 'learning_rate': 0.00045395171832018655, 'epoch': 0.58}
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{'loss': 3.7861, 'grad_norm': 0.2238393872976303, 'learning_rate': 0.00044989696221223635, 'epoch': 0.58}
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{'loss': 3.7818, 'grad_norm': 0.20514371991157532, 'learning_rate': 0.000445845531837065, 'epoch': 0.58}
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{'loss': 3.7845, 'grad_norm': 0.21615807712078094, 'learning_rate': 0.000441797696119979, 'epoch': 0.58}
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{'loss': 3.7792, 'grad_norm': 0.21298275887966156, 'learning_rate': 0.0004377537237476793, 'epoch': 0.59}
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{'loss': 3.7737, 'grad_norm': 0.20505817234516144, 'learning_rate': 0.00043371388315042623, 'epoch': 0.59}
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{'loss': 3.7833, 'grad_norm': 0.20742197334766388, 'learning_rate': 0.00042967844248422153, 'epoch': 0.59}
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{'loss': 3.773, 'grad_norm': 0.20050886273384094, 'learning_rate': 0.00042564766961300916, 'epoch': 0.59}
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{'loss': 3.772, 'grad_norm': 0.2129916101694107, 'learning_rate': 0.00042162183209089473, 'epoch': 0.6}
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{'loss': 3.7736, 'grad_norm': 0.2089225947856903, 'learning_rate': 0.00041760119714438575, 'epoch': 0.6}
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{'loss': 3.7717, 'grad_norm': 0.20950685441493988, 'learning_rate': 0.0004135860316546541, 'epoch': 0.6}
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{'loss': 3.7662, 'grad_norm': 0.2149665206670761, 'learning_rate': 0.0004095766021398206, 'epoch': 0.6}
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{'loss': 3.7766, 'grad_norm': 0.2041858434677124, 'learning_rate': 0.00040557317473726437, 'epoch': 0.6}
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{'loss': 3.7761, 'grad_norm': 0.23098516464233398, 'learning_rate': 0.000401576015185957, 'epoch': 0.61}
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{'loss': 3.769, 'grad_norm': 0.21181854605674744, 'learning_rate': 0.0003975853888088237, 'epoch': 0.61}
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{'loss': 3.7622, 'grad_norm': 0.2049829661846161, 'learning_rate': 0.0003936015604951313, 'epoch': 0.61}
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{'loss': 3.7671, 'grad_norm': 0.22600290179252625, 'learning_rate': 0.00038962479468290583, 'epoch': 0.61}
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{'loss': 3.7571, 'grad_norm': 0.2130744457244873, 'learning_rate': 0.0003856553553413795, 'epoch': 0.62}
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{'loss': 3.7673, 'grad_norm': 0.20758993923664093, 'learning_rate': 0.00038169350595346896, 'epoch': 0.62}
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{'loss': 3.7658, 'grad_norm': 0.2116476446390152, 'learning_rate': 0.00037773950949828583, 'epoch': 0.62}
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{'loss': 3.7573, 'grad_norm': 0.21235235035419464, 'learning_rate': 0.00037379362843368126, 'epoch': 0.62}
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{'loss': 3.7665, 'grad_norm': 0.22047656774520874, 'learning_rate': 0.0003698561246788237, 'epoch': 0.63}
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{'loss': 3.7594, 'grad_norm': 0.20730119943618774, 'learning_rate': 0.0003659272595968135, 'epoch': 0.63}
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{'loss': 3.7567, 'grad_norm': 0.21666917204856873, 'learning_rate': 0.0003620072939773347, 'epoch': 0.63}
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{'loss': 3.7587, 'grad_norm': 0.1974485069513321, 'learning_rate': 0.0003580964880193439, 'epoch': 0.63}
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{'loss': 3.7528, 'grad_norm': 0.21102701127529144, 'learning_rate': 0.00034642162088053754, 'epoch': 0.64}
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{'loss': 3.7513, 'grad_norm': 0.20897677540779114, 'learning_rate': 0.0003425500431398719, 'epoch': 0.64}
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{'loss': 3.7512, 'grad_norm': 0.22081539034843445, 'learning_rate': 0.0003386889165915025, 'epoch': 0.64}
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{'loss': 3.7535, 'grad_norm': 0.21521364152431488, 'learning_rate': 0.00033483849752877394, 'epoch': 0.65}
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{'loss': 3.7524, 'grad_norm': 0.19950926303863525, 'learning_rate': 0.0003309990415342904, 'epoch': 0.65}
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{'loss': 3.7493, 'grad_norm': 0.219803124666214, 'learning_rate': 0.0003271708034629518, 'epoch': 0.65}
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{'loss': 3.7446, 'grad_norm': 0.20303305983543396, 'learning_rate': 0.0003195489967693295, 'epoch': 0.66}
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{'loss': 3.7457, 'grad_norm': 0.20769138634204865, 'learning_rate': 0.00031575593406631694, 'epoch': 0.66}
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{'loss': 3.7472, 'grad_norm': 0.21229270100593567, 'learning_rate': 0.0003119751010914092, 'epoch': 0.66}
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{'loss': 3.7442, 'grad_norm': 0.21795767545700073, 'learning_rate': 0.00030820674880823476, 'epoch': 0.66}
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{'loss': 3.7487, 'grad_norm': 0.21291562914848328, 'learning_rate': 0.0003044511273519802, 'epoch': 0.67}
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{'loss': 3.7466, 'grad_norm': 0.2066812664270401, 'learning_rate': 0.00030070848601278715, 'epoch': 0.67}
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{'loss': 3.7471, 'grad_norm': 0.2061804085969925, 'learning_rate': 0.0002969790732192046, 'epoch': 0.67}
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{'loss': 3.739, 'grad_norm': 0.19732309877872467, 'learning_rate': 0.000293263136521699, 'epoch': 0.67}
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{'loss': 3.741, 'grad_norm': 0.21403934061527252, 'learning_rate': 0.0002895609225762222, 'epoch': 0.67}
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{'loss': 3.7349, 'grad_norm': 0.20244579017162323, 'learning_rate': 0.0002858726771278391, 'epoch': 0.68}
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{'loss': 3.7327, 'grad_norm': 0.2261842042207718, 'learning_rate': 0.00028219864499441584, 'epoch': 0.68}
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{'loss': 3.7299, 'grad_norm': 0.20258717238903046, 'learning_rate': 0.00027853907005036824, 'epoch': 0.68}
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{'loss': 3.7302, 'grad_norm': 0.20479975640773773, 'learning_rate': 0.00027489419521047563, 'epoch': 0.68}
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{'loss': 3.7302, 'grad_norm': 0.21034333109855652, 'learning_rate': 0.0002712642624137552, 'epoch': 0.69}
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{'loss': 3.7338, 'grad_norm': 0.20984427630901337, 'learning_rate': 0.0002676495126074034, 'epoch': 0.69}
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{'loss': 3.7344, 'grad_norm': 0.2076161652803421, 'learning_rate': 0.0002640501857308021, 'epoch': 0.69}
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{'loss': 3.7392, 'grad_norm': 0.21046660840511322, 'learning_rate': 0.0002604665206995922, 'epoch': 0.69}
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{'loss': 3.7416, 'grad_norm': 0.20787328481674194, 'learning_rate': 0.0002568987553898142, 'epoch': 0.7}
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{'loss': 3.7241, 'grad_norm': 0.20701681077480316, 'learning_rate': 0.00025334712662211965, 'epoch': 0.7}
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{'loss': 3.7311, 'grad_norm': 0.21617133915424347, 'learning_rate': 0.0002498118701460503, 'epoch': 0.7}
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{'loss': 3.7232, 'grad_norm': 0.2117692530155182, 'learning_rate': 0.0002462932206243906, 'epoch': 0.7}
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{'loss': 3.7314, 'grad_norm': 0.21344977617263794, 'learning_rate': 0.00024279141161759015, 'epoch': 0.7}
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{'loss': 3.7182, 'grad_norm': 0.22057577967643738, 'learning_rate': 0.00023930667556826173, 'epoch': 0.71}
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{'loss': 3.7248, 'grad_norm': 0.20429687201976776, 'learning_rate': 0.00023583924378575154, 'epoch': 0.71}
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{'loss': 3.722, 'grad_norm': 0.21246246993541718, 'learning_rate': 0.00023238934643078497, 'epoch': 0.71}
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{'loss': 3.7254, 'grad_norm': 0.1994296908378601, 'learning_rate': 0.0002289572125001901, 'epoch': 0.71}
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{'loss': 3.7266, 'grad_norm': 0.21232013404369354, 'learning_rate': 0.00022554306981169614, 'epoch': 0.72}
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{'loss': 3.7214, 'grad_norm': 0.20325839519500732, 'learning_rate': 0.00022214714498881283, 'epoch': 0.72}
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{'loss': 3.7194, 'grad_norm': 0.20564807951450348, 'learning_rate': 0.00021876966344578608, 'epoch': 0.72}
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{'loss': 3.7152, 'grad_norm': 0.21158863604068756, 'learning_rate': 0.00021541084937263684, 'epoch': 0.72}
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{'loss': 3.7177, 'grad_norm': 0.20968638360500336, 'learning_rate': 0.00021207092572027864, 'epoch': 0.73}
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{'loss': 3.7172, 'grad_norm': 0.21512188017368317, 'learning_rate': 0.00020875011418571983, 'epoch': 0.73}
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{'loss': 3.7159, 'grad_norm': 0.21577095985412598, 'learning_rate': 0.00020544863519734647, 'epoch': 0.73}
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{'loss': 3.7165, 'grad_norm': 0.1993643343448639, 'learning_rate': 0.000202166707900292, 'epoch': 0.73}
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{'loss': 3.7129, 'grad_norm': 0.19936247169971466, 'learning_rate': 0.0001989045501418899, 'epoch': 0.74}
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{'loss': 3.7127, 'grad_norm': 0.20587675273418427, 'learning_rate': 0.00019566237845721407, 'epoch': 0.74}
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{'loss': 3.7083, 'grad_norm': 0.21518193185329437, 'learning_rate': 0.00019244040805470552, 'epoch': 0.74}
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{'loss': 3.7142, 'grad_norm': 0.2125559151172638, 'learning_rate': 0.0001892388528018869, 'epoch': 0.74}
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{'loss': 3.7135, 'grad_norm': 0.1997227966785431, 'learning_rate': 0.00018605792521116728, 'epoch': 0.74}
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{'loss': 3.7103, 'grad_norm': 0.28065919876098633, 'learning_rate': 0.0001828978364257349, 'epoch': 0.75}
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{'loss': 3.7057, 'grad_norm': 0.22211341559886932, 'learning_rate': 0.0001797587962055431, 'epoch': 0.75}
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{'loss': 3.7097, 'grad_norm': 0.20488256216049194, 'learning_rate': 0.00017664101291338597, 'epoch': 0.75}
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{'loss': 3.7045, 'grad_norm': 0.2008345127105713, 'learning_rate': 0.00017354469350106845, 'epoch': 0.75}
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{'loss': 3.7051, 'grad_norm': 0.2025621086359024, 'learning_rate': 0.00017047004349566842, 'epoch': 0.76}
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{'loss': 3.7007, 'grad_norm': 0.2042194902896881, 'learning_rate': 0.00016741726698589533, 'epoch': 0.76}
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{'loss': 3.7039, 'grad_norm': 0.1996219903230667, 'learning_rate': 0.00016438656660854202, 'epoch': 0.76}
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{'loss': 3.7042, 'grad_norm': 0.2138223499059677, 'learning_rate': 0.00016137814353503523, 'epoch': 0.76}
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{'loss': 3.7058, 'grad_norm': 0.20945192873477936, 'learning_rate': 0.00015839219745808174, 'epoch': 0.77}
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{'loss': 3.7003, 'grad_norm': 0.2007862627506256, 'learning_rate': 0.0001554289265784129, 'epoch': 0.77}
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{'loss': 3.7052, 'grad_norm': 0.20554275810718536, 'learning_rate': 0.00015248852759162934, 'epoch': 0.77}
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{'loss': 3.702, 'grad_norm': 0.2057362049818039, 'learning_rate': 0.00014957119567514355, 'epoch': 0.77}
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{'loss': 3.7042, 'grad_norm': 0.20778384804725647, 'learning_rate': 0.00014667712447522592, 'epoch': 0.77}
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{'loss': 3.6977, 'grad_norm': 0.20117060840129852, 'learning_rate': 0.0001438065060941493, 'epoch': 0.78}
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{'loss': 3.709, 'grad_norm': 0.20583467185497284, 'learning_rate': 0.0001409595310774391, 'epoch': 0.78}
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{'loss': 3.7028, 'grad_norm': 0.20341756939888, 'learning_rate': 0.000138136388401224, 'epoch': 0.78}
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{'loss': 3.6934, 'grad_norm': 0.20233885943889618, 'learning_rate': 0.0001353372654596935, 'epoch': 0.78}
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{'loss': 3.7015, 'grad_norm': 0.19619029760360718, 'learning_rate': 0.0001325623480526576, 'epoch': 0.79}
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{'loss': 3.702, 'grad_norm': 0.20964138209819794, 'learning_rate': 0.00012981182037321516, 'epoch': 0.79}
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{'loss': 3.6904, 'grad_norm': 0.19663332402706146, 'learning_rate': 0.00012708586499552644, 'epoch': 0.79}
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{'loss': 3.7009, 'grad_norm': 0.20262502133846283, 'learning_rate': 0.000124384662862695, 'epoch': 0.79}
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{'loss': 3.6867, 'grad_norm': 0.20111532509326935, 'learning_rate': 0.00012170839327475707, 'epoch': 0.8}
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{'loss': 3.692, 'grad_norm': 0.20438751578330994, 'learning_rate': 0.00011905723387677897, 'epoch': 0.8}
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{'loss': 3.6933, 'grad_norm': 0.20212812721729279, 'learning_rate': 0.00011643136064706706, 'epoch': 0.8}
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{'loss': 3.6923, 'grad_norm': 0.21422554552555084, 'learning_rate': 0.00011383094788548492, 'epoch': 0.8}
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{'loss': 3.6954, 'grad_norm': 0.20308765769004822, 'learning_rate': 0.00011125616820188544, 'epoch': 0.81}
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{'loss': 3.6921, 'grad_norm': 0.20140114426612854, 'learning_rate': 0.00010870719250465161, 'epoch': 0.81}
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{'loss': 3.6914, 'grad_norm': 0.20074278116226196, 'learning_rate': 0.00010618418998935358, 'epoch': 0.81}
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{'loss': 3.6903, 'grad_norm': 0.20040340721607208, 'learning_rate': 0.00010368732812751652, 'epoch': 0.81}
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{'loss': 3.6866, 'grad_norm': 0.20556968450546265, 'learning_rate': 0.00010121677265550522, 'epoch': 0.81}
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{'loss': 3.6833, 'grad_norm': 0.19644449651241302, 'learning_rate': 9.877268756352204e-05, 'epoch': 0.82}
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{'loss': 3.6905, 'grad_norm': 0.2021641880273819, 'learning_rate': 9.635523508472227e-05, 'epoch': 0.82}
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{'loss': 3.6882, 'grad_norm': 0.20365110039710999, 'learning_rate': 9.396457568444517e-05, 'epoch': 0.82}
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{'loss': 3.6909, 'grad_norm': 0.2037484496831894, 'learning_rate': 9.160086804956214e-05, 'epoch': 0.82}
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{'loss': 3.6882, 'grad_norm': 0.2024458795785904, 'learning_rate': 8.926426907794455e-05, 'epoch': 0.83}
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{'loss': 3.6918, 'grad_norm': 0.1989620327949524, 'learning_rate': 8.695493386804792e-05, 'epoch': 0.83}
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{'loss': 3.6824, 'grad_norm': 0.20173591375350952, 'learning_rate': 8.467301570861784e-05, 'epoch': 0.83}
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{'loss': 3.6834, 'grad_norm': 0.20509269833564758, 'learning_rate': 8.241866606851428e-05, 'epoch': 0.83}
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{'loss': 3.6869, 'grad_norm': 0.2080000340938568, 'learning_rate': 8.019203458665802e-05, 'epoch': 0.84}
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{'loss': 3.6825, 'grad_norm': 0.202130526304245, 'learning_rate': 7.79932690620972e-05, 'epoch': 0.84}
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{'loss': 3.6876, 'grad_norm': 0.20033104717731476, 'learning_rate': 7.582251544419754e-05, 'epoch': 0.84}
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{'loss': 3.6933, 'grad_norm': 0.19894279539585114, 'learning_rate': 7.156561841942638e-05, 'epoch': 0.84}
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{'loss': 3.6879, 'grad_norm': 0.19803209602832794, 'learning_rate': 6.947975757629937e-05, 'epoch': 0.85}
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{'loss': 3.6857, 'grad_norm': 0.20688019692897797, 'learning_rate': 6.742247374856664e-05, 'epoch': 0.85}
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{'loss': 3.6878, 'grad_norm': 0.19367839395999908, 'learning_rate': 6.539390349434054e-05, 'epoch': 0.85}
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{'loss': 3.6837, 'grad_norm': 0.20150558650493622, 'learning_rate': 6.339418146578746e-05, 'epoch': 0.85}
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{'loss': 3.6806, 'grad_norm': 0.19965173304080963, 'learning_rate': 6.142344040019049e-05, 'epoch': 0.86}
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{'loss': 3.6853, 'grad_norm': 0.20756445825099945, 'learning_rate': 5.948181111113765e-05, 'epoch': 0.86}
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{'loss': 3.6796, 'grad_norm': 0.203931987285614, 'learning_rate': 5.7569422479840036e-05, 'epoch': 0.86}
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{'loss': 3.6751, 'grad_norm': 0.1984408050775528, 'learning_rate': 5.5686401446575555e-05, 'epoch': 0.86}
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{'loss': 3.6795, 'grad_norm': 0.19637839496135712, 'learning_rate': 5.383287300226419e-05, 'epoch': 0.87}
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{'loss': 3.6793, 'grad_norm': 0.1984408050775528, 'learning_rate': 5.2008960180170264e-05, 'epoch': 0.87}
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{'loss': 3.6773, 'grad_norm': 0.19666090607643127, 'learning_rate': 5.021478404773666e-05, 'epoch': 0.87}
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{'loss': 3.6733, 'grad_norm': 0.19814348220825195, 'learning_rate': 4.8450463698547996e-05, 'epoch': 0.87}
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{'loss': 3.678, 'grad_norm': 0.19885480403900146, 'learning_rate': 4.6716116244425786e-05, 'epoch': 0.88}
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{'loss': 3.6744, 'grad_norm': 0.19856145977973938, 'learning_rate': 4.5011856807654794e-05, 'epoch': 0.88}
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{'loss': 3.6752, 'grad_norm': 0.19813941419124603, 'learning_rate': 4.333779851334108e-05, 'epoch': 0.88}
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{'loss': 3.6752, 'grad_norm': 0.19872236251831055, 'learning_rate': 4.169405248190361e-05, 'epoch': 0.88}
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{'loss': 3.6734, 'grad_norm': 0.20788125693798065, 'learning_rate': 4.0080727821697695e-05, 'epoch': 0.88}
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{'loss': 3.6793, 'grad_norm': 0.19586370885372162, 'learning_rate': 3.849793162177323e-05, 'epoch': 0.89}
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{'loss': 3.6757, 'grad_norm': 0.2003939002752304, 'learning_rate': 3.69457689447657e-05, 'epoch': 0.89}
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{'loss': 3.6796, 'grad_norm': 0.19392305612564087, 'learning_rate': 3.5424342819923015e-05, 'epoch': 0.89}
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{'loss': 3.676, 'grad_norm': 0.19719606637954712, 'learning_rate': 3.393375423626599e-05, 'epoch': 0.89}
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{'loss': 3.6711, 'grad_norm': 0.19079309701919556, 'learning_rate': 3.247410213588553e-05, 'epoch': 0.9}
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{'loss': 3.6748, 'grad_norm': 0.20690591633319855, 'learning_rate': 3.1045483407374505e-05, 'epoch': 0.9}
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{'loss': 3.6772, 'grad_norm': 0.19457007944583893, 'learning_rate': 2.9647992879397012e-05, 'epoch': 0.9}
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{'loss': 3.6748, 'grad_norm': 0.1965537667274475, 'learning_rate': 2.828172331439327e-05, 'epoch': 0.9}
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{'loss': 3.6753, 'grad_norm': 0.20015136897563934, 'learning_rate': 2.6946765402422858e-05, 'epoch': 0.91}
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{'loss': 3.679, 'grad_norm': 0.1981126070022583, 'learning_rate': 2.5643207755144615e-05, 'epoch': 0.91}
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{'loss': 3.6744, 'grad_norm': 0.1973486840724945, 'learning_rate': 2.4371136899934532e-05, 'epoch': 0.91}
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{'loss': 3.6701, 'grad_norm': 0.19702301919460297, 'learning_rate': 2.3130637274142775e-05, 'epoch': 0.91}
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{'loss': 3.6698, 'grad_norm': 0.1986294537782669, 'learning_rate': 2.1921791219488398e-05, 'epoch': 0.91}
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{'loss': 3.6711, 'grad_norm': 0.19484589993953705, 'learning_rate': 2.0744678976594156e-05, 'epoch': 0.92}
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{'loss': 3.662, 'grad_norm': 0.1955128163099289, 'learning_rate': 1.959937867965983e-05, 'epoch': 0.92}
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{'loss': 3.6738, 'grad_norm': 0.19075419008731842, 'learning_rate': 1.8485966351276417e-05, 'epoch': 0.92}
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{'loss': 3.6637, 'grad_norm': 0.19542671740055084, 'learning_rate': 1.7404515897379126e-05, 'epoch': 0.92}
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{'loss': 3.6679, 'grad_norm': 0.19671228528022766, 'learning_rate': 1.6355099102342562e-05, 'epoch': 0.93}
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{'loss': 3.6695, 'grad_norm': 0.1922970861196518, 'learning_rate': 1.5337785624215004e-05, 'epoch': 0.93}
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{'loss': 3.6626, 'grad_norm': 0.19567406177520752, 'learning_rate': 1.435264299009531e-05, 'epoch': 0.93}
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{'loss': 3.677, 'grad_norm': 0.19261209666728973, 'learning_rate': 1.339973659165028e-05, 'epoch': 0.93}
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{'loss': 3.6651, 'grad_norm': 0.19262836873531342, 'learning_rate': 1.2479129680773971e-05, 'epoch': 0.94}
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{'loss': 3.6732, 'grad_norm': 0.19460439682006836, 'learning_rate': 1.1590883365389549e-05, 'epoch': 0.94}
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{'loss': 3.6637, 'grad_norm': 0.19693857431411743, 'learning_rate': 1.0735056605392756e-05, 'epoch': 0.94}
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{'loss': 3.6724, 'grad_norm': 0.19636833667755127, 'learning_rate': 9.911706208738547e-06, 'epoch': 0.94}
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{'loss': 3.675, 'grad_norm': 0.1976543664932251, 'learning_rate': 9.120886827669928e-06, 'epoch': 0.95}
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{'loss': 3.6749, 'grad_norm': 0.19580678641796112, 'learning_rate': 8.3626509550907e-06, 'epoch': 0.95}
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{'loss': 3.6741, 'grad_norm': 0.19619998335838318, 'learning_rate': 7.637048921080636e-06, 'epoch': 0.95}
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{'loss': 3.6819, 'grad_norm': 0.19207993149757385, 'learning_rate': 6.9441288895552015e-06, 'epoch': 0.95}
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{'loss': 3.6801, 'grad_norm': 0.19403386116027832, 'learning_rate': 6.283936855068006e-06, 'epoch': 0.95}
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{'loss': 3.6697, 'grad_norm': 0.19288146495819092, 'learning_rate': 5.656516639758136e-06, 'epoch': 0.96}
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{'loss': 3.6741, 'grad_norm': 0.1951368749141693, 'learning_rate': 5.0619098904411964e-06, 'epoch': 0.96}
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{'loss': 3.6674, 'grad_norm': 0.19309432804584503, 'learning_rate': 4.500156075844919e-06, 'epoch': 0.96}
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{'loss': 3.6723, 'grad_norm': 0.1945876032114029, 'learning_rate': 3.971292483989309e-06, 'epoch': 0.96}
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{'loss': 3.6769, 'grad_norm': 0.19029711186885834, 'learning_rate': 3.4753542197114575e-06, 'epoch': 0.97}
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{'loss': 3.6778, 'grad_norm': 0.19272814691066742, 'learning_rate': 3.0123742023356325e-06, 'epoch': 0.97}
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{'loss': 3.672, 'grad_norm': 0.19305270910263062, 'learning_rate': 2.582383163487745e-06, 'epoch': 0.97}
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{'loss': 3.666, 'grad_norm': 0.1948838233947754, 'learning_rate': 2.1854096450558136e-06, 'epoch': 0.97}
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{'loss': 3.6748, 'grad_norm': 0.19187714159488678, 'learning_rate': 1.8214799972953166e-06, 'epoch': 0.98}
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{'loss': 3.6704, 'grad_norm': 0.19264216721057892, 'learning_rate': 1.490618377079922e-06, 'epoch': 0.98}
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{'loss': 3.6703, 'grad_norm': 0.19271817803382874, 'learning_rate': 1.1928467462982706e-06, 'epoch': 0.98}
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{'loss': 3.6725, 'grad_norm': 0.1987934112548828, 'learning_rate': 9.281848703961426e-07, 'epoch': 0.98}
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{'loss': 3.6712, 'grad_norm': 0.1921512335538864, 'learning_rate': 6.966503170642292e-07, 'epoch': 0.98}
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{'loss': 3.6721, 'grad_norm': 0.19429098069667816, 'learning_rate': 4.982584550723978e-07, 'epoch': 0.99}
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{'loss': 3.6659, 'grad_norm': 0.1904834657907486, 'learning_rate': 3.3302245324928757e-07, 'epoch': 0.99}
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{'loss': 3.6715, 'grad_norm': 0.19539688527584076, 'learning_rate': 2.0095327960817367e-07, 'epoch': 0.99}
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{'loss': 3.6772, 'grad_norm': 0.19224008917808533, 'learning_rate': 1.0205970061916148e-07, 'epoch': 0.99}
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{'loss': 3.6748, 'grad_norm': 0.19364675879478455, 'learning_rate': 3.6348280627040987e-08, 'epoch': 1.0}
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{'loss': 3.6587, 'grad_norm': 0.19537560641765594, 'learning_rate': 3.823381415801741e-09, 'epoch': 1.0}
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{'train_runtime': 7001.8355, 'train_samples_per_second': 1566.659, 'train_steps_per_second': 1.53, 'train_loss': 4.054233100184582, '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.