slurm submission log: 2024-05-17 11:42:20.474744
created following sbatch script: 

###############################

#!/bin/bash

#SBATCH --account=nlp
#SBATCH --cpus-per-task=16
#SBATCH --dependency=afterok:7625431
#SBATCH --gres=gpu:2
#SBATCH --job-name=tthrush-job-4361722
#SBATCH --mem=400G
#SBATCH --nodelist=sphinx2
#SBATCH --open-mode=append
#SBATCH --output=/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_more_data/pythia-70m_lambada/train_job_output.txt
#SBATCH --partition=sphinx
#SBATCH --time=14-0

# activate your desired anaconda environment
. /nlp/scr/tthrush/miniconda3/envs/pretraining-coreset-selection/etc/profile.d/conda.sh ; conda activate pretraining-coreset-selection

# cd to working directory
cd .

# launch commands
srun --unbuffered run_as_child_processes 'torchrun --master_port 29506 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data/lambada --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_more_data/pythia-70m_lambada --output_hub_id pythia-70m_lambada --model_id EleutherAI/pythia-70m --num_train_epochs 1 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2'

###############################

submission to slurm complete!


###############################
slurm submission output

Submitted batch job 7625432



###############################

/var/lib/slurm/slurmd/job7625432/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

    $ conda init <SHELL_NAME>

Currently supported shells are:
  - bash
  - fish
  - tcsh
  - xonsh
  - zsh
  - powershell

See 'conda init --help' for more information and options.

IMPORTANT: You may need to close and restart your shell after running 'conda init'.


###############################
start time: 2024-05-18 00:12:23.054910
machine: sphinx2
conda env: pretraining-coreset-selection
###############################
running following processes

	torchrun --master_port 29506 --nproc_per_node=2 train_llm.py --dataset_id /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data/lambada --output_dir /juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_more_data/pythia-70m_lambada --output_hub_id pythia-70m_lambada --model_id EleutherAI/pythia-70m --num_train_epochs 1 --learning_rate 1e-3 --warmup_ratio=0.1 --gradient_accumulation_steps 2


###############################
command outputs: 


[2024-05-18 00:12:25,027] torch.distributed.run: [WARNING] 
[2024-05-18 00:12:25,027] torch.distributed.run: [WARNING] *****************************************
[2024-05-18 00:12:25,027] 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. 
[2024-05-18 00:12:25,027] torch.distributed.run: [WARNING] *****************************************
05/18/2024 00:12:29 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data/lambada', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_more_data/pythia-70m_lambada', output_hub_id='pythia-70m_lambada', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)
05/18/2024 00:12:29 - INFO - __main__ - Script parameters ScriptArguments(dataset_id='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/train_data_more_data/lambada', output_dir='/juice5/scr5/tthrush/pretraining-coreset-selection/llm_pretraining/llms_more_data/pythia-70m_lambada', output_hub_id='pythia-70m_lambada', hf_hub_token=True, model_id='EleutherAI/pythia-70m', per_device_train_batch_size=256, num_train_epochs=1, learning_rate=0.001, gradient_accumulation_steps=2, from_scratch=True, warmup_ratio=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, weight_decay=0.01, lr_scheduler_type='cosine', local_rank=0, resume_from_checkpoint=False, deepspeed=None, peft=False)

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[rank1]:[W reducer.cpp:1360] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration,  which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())

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                                                     {'loss': 10.6379, 'grad_norm': 1.518687129020691, 'learning_rate': 2.3386342376052384e-05, 'epoch': 0.0}


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                                                     {'loss': 8.4021, 'grad_norm': 0.8535653948783875, 'learning_rate': 9.354536950420954e-05, 'epoch': 0.01}

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{'loss': 7.7462, 'grad_norm': 0.47506141662597656, 'learning_rate': 0.00011693171188026193, 'epoch': 0.01}

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{'loss': 7.2887, 'grad_norm': 0.4157545268535614, 'learning_rate': 0.0001403180542563143, 'epoch': 0.01}

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                                                     {'loss': 6.6194, 'grad_norm': 0.6208123564720154, 'learning_rate': 0.00018709073900841907, 'epoch': 0.02}

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{'loss': 6.3773, 'grad_norm': 0.6479279398918152, 'learning_rate': 0.00021047708138447147, 'epoch': 0.02}

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                                                     {'loss': 6.1815, 'grad_norm': 0.599463701248169, 'learning_rate': 0.00023386342376052386, 'epoch': 0.02}


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{'loss': 6.0129, 'grad_norm': 0.7391013503074646, 'learning_rate': 0.00025724976613657625, 'epoch': 0.03}

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{'loss': 5.867, 'grad_norm': 0.7351891994476318, 'learning_rate': 0.0002806361085126286, 'epoch': 0.03}

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                                                     {'loss': 5.7403, 'grad_norm': 0.6719109416007996, 'learning_rate': 0.00030402245088868103, 'epoch': 0.03}

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{'loss': 5.6318, 'grad_norm': 0.5963531732559204, 'learning_rate': 0.00032740879326473337, 'epoch': 0.03}

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{'loss': 5.3684, 'grad_norm': 0.8292851448059082, 'learning_rate': 0.0003975678203928906, 'epoch': 0.04}

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{'loss': 5.2225, 'grad_norm': 0.7135836482048035, 'learning_rate': 0.0004443405051449954, 'epoch': 0.04}

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{'loss': 4.9936, 'grad_norm': 0.5443073511123657, 'learning_rate': 0.0005378858746492049, 'epoch': 0.05}

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{'loss': 4.7847, 'grad_norm': 0.3903139531612396, 'learning_rate': 0.0006548175865294667, 'epoch': 0.07}

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                                                     {'loss': 4.7519, 'grad_norm': 0.41105523705482483, 'learning_rate': 0.0006782039289055192, 'epoch': 0.07}


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{'loss': 4.494, 'grad_norm': 0.36147475242614746, 'learning_rate': 0.0009354536950420954, 'epoch': 0.09}

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{'loss': 4.4688, 'grad_norm': 0.3146020770072937, 'learning_rate': 0.0009588400374181479, 'epoch': 0.1}

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{'loss': 4.4544, 'grad_norm': 0.34989291429519653, 'learning_rate': 0.0009822263797942, 'epoch': 0.1}

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{'loss': 4.4193, 'grad_norm': 0.2870602607727051, 'learning_rate': 0.0009999743408927195, 'epoch': 0.1}

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                                                      {'loss': 4.3789, 'grad_norm': 0.2916446328163147, 'learning_rate': 0.0009998248272504882, 'epoch': 0.11}

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{'loss': 4.3142, 'grad_norm': 0.2728389799594879, 'learning_rate': 0.0009991255149608528, 'epoch': 0.12}

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{'loss': 4.2998, 'grad_norm': 0.2711522877216339, 'learning_rate': 0.0009988673590077238, 'epoch': 0.12}

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{'loss': 4.1775, 'grad_norm': 0.24959181249141693, 'learning_rate': 0.0009950482550633215, 'epoch': 0.14}

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{'loss': 4.1442, 'grad_norm': 0.27838432788848877, 'learning_rate': 0.0009931792360859792, 'epoch': 0.15}

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{'loss': 4.1281, 'grad_norm': 0.2294573187828064, 'learning_rate': 0.0009917685524442382, 'epoch': 0.15}

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                                                      {'loss': 4.1065, 'grad_norm': 0.24439358711242676, 'learning_rate': 0.0009902265663133602, 'epoch': 0.16}


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{'loss': 4.105, 'grad_norm': 0.2592258155345917, 'learning_rate': 0.0009894064621077375, 'epoch': 0.16}

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                                                      {'loss': 4.0806, 'grad_norm': 0.23648607730865479, 'learning_rate': 0.0009876683051274124, 'epoch': 0.16}


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{'loss': 4.0583, 'grad_norm': 0.24888846278190613, 'learning_rate': 0.0009848170847181403, 'epoch': 0.17}

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                                                      {'loss': 4.0542, 'grad_norm': 0.23744124174118042, 'learning_rate': 0.0009838018668590573, 'epoch': 0.17}

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                                                      {'loss': 4.0497, 'grad_norm': 0.22908669710159302, 'learning_rate': 0.0009816746179122904, 'epoch': 0.18}


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                                                      {'loss': 4.0451, 'grad_norm': 0.25135472416877747, 'learning_rate': 0.0009805627288211524, 'epoch': 0.18}


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{'loss': 4.036, 'grad_norm': 0.22280021011829376, 'learning_rate': 0.0009794187615627694, 'epoch': 0.18}

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{'loss': 4.0344, 'grad_norm': 0.22722424566745758, 'learning_rate': 0.0009782427924983968, 'epoch': 0.18}

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{'loss': 4.021, 'grad_norm': 0.2283782809972763, 'learning_rate': 0.0009757951650722661, 'epoch': 0.19}

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{'loss': 3.9983, 'grad_norm': 0.23825807869434357, 'learning_rate': 0.000971885741964458, 'epoch': 0.2}

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{'loss': 3.9916, 'grad_norm': 0.22821089625358582, 'learning_rate': 0.0009691218200690053, 'epoch': 0.2}

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{'loss': 3.9797, 'grad_norm': 0.22974920272827148, 'learning_rate': 0.0009662326423751136, 'epoch': 0.21}

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{'loss': 3.9739, 'grad_norm': 0.21651457250118256, 'learning_rate': 0.0009616657177703876, 'epoch': 0.21}

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                                                      {'loss': 3.9492, 'grad_norm': 0.2225293070077896, 'learning_rate': 0.0009551455676283627, 'epoch': 0.22}

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{'loss': 3.9438, 'grad_norm': 0.22597463428974152, 'learning_rate': 0.0009534392991207893, 'epoch': 0.22}

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{'loss': 3.9483, 'grad_norm': 0.21352504193782806, 'learning_rate': 0.0009517027629690559, 'epoch': 0.23}

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{'loss': 3.9319, 'grad_norm': 0.22187572717666626, 'learning_rate': 0.0009463127178640994, 'epoch': 0.23}

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                                                      {'loss': 3.9206, 'grad_norm': 0.21757052838802338, 'learning_rate': 0.0009406545572679153, 'epoch': 0.24}

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{'loss': 3.9144, 'grad_norm': 0.22559185326099396, 'learning_rate': 0.0009387095054051274, 'epoch': 0.24}

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{'loss': 3.9063, 'grad_norm': 0.23357582092285156, 'learning_rate': 0.0009347316802333359, 'epoch': 0.25}

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{'loss': 3.9031, 'grad_norm': 0.2126639038324356, 'learning_rate': 0.0009306377814504165, 'epoch': 0.25}

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{'loss': 3.8964, 'grad_norm': 0.23009715974330902, 'learning_rate': 0.0009264289021297221, 'epoch': 0.26}

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                                                      {'loss': 3.9001, 'grad_norm': 0.20718076825141907, 'learning_rate': 0.0009242816947557767, 'epoch': 0.26}


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                                                      {'loss': 3.8965, 'grad_norm': 0.2413903921842575, 'learning_rate': 0.0009199024612151008, 'epoch': 0.26}

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{'loss': 3.8775, 'grad_norm': 0.23304373025894165, 'learning_rate': 0.0009108088507230948, 'epoch': 0.27}

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{'loss': 3.8717, 'grad_norm': 0.2135021984577179, 'learning_rate': 0.0009060969017710476, 'epoch': 0.28}

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{'loss': 3.8553, 'grad_norm': 0.21128380298614502, 'learning_rate': 0.0008938454796549082, 'epoch': 0.29}

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{'loss': 3.8615, 'grad_norm': 0.22659720480442047, 'learning_rate': 0.000891315663043654, 'epoch': 0.29}

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                                                      {'loss': 3.8558, 'grad_norm': 0.2236180305480957, 'learning_rate': 0.0008861778379934982, 'epoch': 0.3}


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{'loss': 3.8461, 'grad_norm': 0.2249985933303833, 'learning_rate': 0.000883570172510888, 'epoch': 0.3}

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{'loss': 3.8447, 'grad_norm': 0.23057498037815094, 'learning_rate': 0.0008809369032362939, 'epoch': 0.3}

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                                                      {'loss': 3.8384, 'grad_norm': 0.21458952128887177, 'learning_rate': 0.0008782782059437559, 'epoch': 0.3}


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{'loss': 3.835, 'grad_norm': 0.2155744582414627, 'learning_rate': 0.0008701513290879668, 'epoch': 0.31}

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{'loss': 3.8357, 'grad_norm': 0.24934151768684387, 'learning_rate': 0.0008673927112327234, 'epoch': 0.31}

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{'loss': 3.8294, 'grad_norm': 0.2154206782579422, 'learning_rate': 0.000864609569451406, 'epoch': 0.32}

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{'loss': 3.8278, 'grad_norm': 0.21678951382637024, 'learning_rate': 0.0008561148664436948, 'epoch': 0.32}

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{'loss': 3.8203, 'grad_norm': 0.20912215113639832, 'learning_rate': 0.0008532355029236307, 'epoch': 0.33}

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{'loss': 3.8138, 'grad_norm': 0.20994342863559723, 'learning_rate': 0.0008444567155371176, 'epoch': 0.33}

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                                                    {'loss': 3.8053, 'grad_norm': 0.22371667623519897, 'learning_rate': 0.0008324307086141438, 'epoch': 0.34}

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{'loss': 3.8076, 'grad_norm': 0.2062297761440277, 'learning_rate': 0.0008231775093601584, 'epoch': 0.35}

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{'loss': 3.7968, 'grad_norm': 0.20821678638458252, 'learning_rate': 0.0008169005041617021, 'epoch': 0.35}

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{'loss': 3.7812, 'grad_norm': 0.20536939799785614, 'learning_rate': 0.0008105388863445693, 'epoch': 0.36}

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{'loss': 3.7869, 'grad_norm': 0.20998729765415192, 'learning_rate': 0.0008073268776325152, 'epoch': 0.36}

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{'loss': 3.7777, 'grad_norm': 0.20530767738819122, 'learning_rate': 0.0008040943544644116, 'epoch': 0.36}

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{'loss': 3.7699, 'grad_norm': 0.22036899626255035, 'learning_rate': 0.0007876316210265521, 'epoch': 0.37}

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{'loss': 3.7742, 'grad_norm': 0.20299334824085236, 'learning_rate': 0.0007809105815091867, 'epoch': 0.38}

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{'loss': 3.778, 'grad_norm': 0.20165860652923584, 'learning_rate': 0.0007775218225718394, 'epoch': 0.38}

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{'loss': 3.7744, 'grad_norm': 0.21162648499011993, 'learning_rate': 0.0007741145387033967, 'epoch': 0.38}

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{'loss': 3.7656, 'grad_norm': 0.21876271069049835, 'learning_rate': 0.0007672453071565586, 'epoch': 0.39}

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{'loss': 3.7602, 'grad_norm': 0.22859026491641998, 'learning_rate': 0.0007603047209574854, 'epoch': 0.39}

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                                                    {'loss': 3.7628, 'grad_norm': 0.21450260281562805, 'learning_rate': 0.0007568082482390682, 'epoch': 0.4}

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{'loss': 3.7562, 'grad_norm': 0.21526353061199188, 'learning_rate': 0.0007532946332467235, 'epoch': 0.4}

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{'loss': 3.751, 'grad_norm': 0.22080130875110626, 'learning_rate': 0.0007426532856357045, 'epoch': 0.4}

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{'loss': 3.7484, 'grad_norm': 0.21393784880638123, 'learning_rate': 0.0007318661678006427, 'epoch': 0.41}

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{'loss': 3.7553, 'grad_norm': 0.21232718229293823, 'learning_rate': 0.0007282391860581049, 'epoch': 0.41}

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{'loss': 3.7477, 'grad_norm': 0.2059030830860138, 'learning_rate': 0.0007245969690625126, 'epoch': 0.42}

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{'loss': 3.745, 'grad_norm': 0.2034536451101303, 'learning_rate': 0.0007172678028031901, 'epoch': 0.42}

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{'loss': 3.7431, 'grad_norm': 0.21141181886196136, 'learning_rate': 0.0007061658992620613, 'epoch': 0.43}

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                                                    {'loss': 3.7305, 'grad_norm': 0.21654845774173737, 'learning_rate': 0.0006986954093387361, 'epoch': 0.43}


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{'loss': 3.7225, 'grad_norm': 0.22168032824993134, 'learning_rate': 0.0006873908295562602, 'epoch': 0.44}

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                                                    {'loss': 3.7271, 'grad_norm': 0.21540647745132446, 'learning_rate': 0.0006835972829129873, 'epoch': 0.44}


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                                                    {'loss': 3.7189, 'grad_norm': 0.2164423167705536, 'learning_rate': 0.000679791480919905, 'epoch': 0.44}


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{'loss': 3.7186, 'grad_norm': 0.21361175179481506, 'learning_rate': 0.0006721441278537161, 'epoch': 0.45}

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{'loss': 3.7154, 'grad_norm': 0.2031516432762146, 'learning_rate': 0.0006644508122054031, 'epoch': 0.45}

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                                                    {'loss': 3.6994, 'grad_norm': 0.2008499652147293, 'learning_rate': 0.0006450299456639985, 'epoch': 0.47}

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{'loss': 3.7059, 'grad_norm': 0.21612754464149475, 'learning_rate': 0.0006214083583911186, 'epoch': 0.48}

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                                                    {'loss': 3.6933, 'grad_norm': 0.2120669186115265, 'learning_rate': 0.0006174415244767953, 'epoch': 0.48}


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                                                    {'loss': 3.6999, 'grad_norm': 0.22484762966632843, 'learning_rate': 0.0006134668511928376, 'epoch': 0.48}

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{'loss': 3.6996, 'grad_norm': 0.20833349227905273, 'learning_rate': 0.000605495048279383, 'epoch': 0.49}

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{'loss': 3.6858, 'grad_norm': 0.21420985460281372, 'learning_rate': 0.000597495078126763, 'epoch': 0.49}

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{'loss': 3.6969, 'grad_norm': 0.22893981635570526, 'learning_rate': 0.0005814191870410933, 'epoch': 0.5}

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{'loss': 3.6666, 'grad_norm': 0.20613126456737518, 'learning_rate': 0.0005245822889824633, 'epoch': 0.54}

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                                                    {'loss': 3.668, 'grad_norm': 0.22501885890960693, 'learning_rate': 0.0005164190835329964, 'epoch': 0.54}


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{'loss': 3.6593, 'grad_norm': 0.2032850682735443, 'learning_rate': 0.0005123357005676156, 'epoch': 0.54}

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{'loss': 3.6617, 'grad_norm': 0.218989297747612, 'learning_rate': 0.0004837442325565422, 'epoch': 0.56}

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{'loss': 3.6541, 'grad_norm': 0.22366584837436676, 'learning_rate': 0.0004674241234809751, 'epoch': 0.57}

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{'loss': 3.6487, 'grad_norm': 0.2054712325334549, 'learning_rate': 0.00044707494803155137, 'epoch': 0.58}

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                                                      {'loss': 3.6279, 'grad_norm': 0.21333785355091095, 'learning_rate': 0.0004066753292465861, 'epoch': 0.6}

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{'loss': 3.6309, 'grad_norm': 0.21840351819992065, 'learning_rate': 0.00040266519392417936, 'epoch': 0.61}

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{'loss': 3.6279, 'grad_norm': 0.20090648531913757, 'learning_rate': 0.0003946646821898418, 'epoch': 0.61}

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{'loss': 3.6258, 'grad_norm': 0.20445843040943146, 'learning_rate': 0.00038271731370291583, 'epoch': 0.62}

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                                                      {'loss': 3.6257, 'grad_norm': 0.21112240850925446, 'learning_rate': 0.0003708404009834161, 'epoch': 0.62}


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{'loss': 3.62, 'grad_norm': 0.22026865184307098, 'learning_rate': 0.00036296512652851323, 'epoch': 0.63}

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{'loss': 3.6174, 'grad_norm': 0.21252231299877167, 'learning_rate': 0.00035904107890373196, 'epoch': 0.63}

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{'loss': 3.6015, 'grad_norm': 0.20563794672489166, 'learning_rate': 0.0002977120114920343, 'epoch': 0.67}

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{'loss': 3.5914, 'grad_norm': 0.20954489707946777, 'learning_rate': 0.00029398297770374336, 'epoch': 0.67}

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{'loss': 3.5899, 'grad_norm': 0.20955775678157806, 'learning_rate': 0.0002792068368154043, 'epoch': 0.68}

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{'loss': 3.5878, 'grad_norm': 0.20695380866527557, 'learning_rate': 0.0002719062117197888, 'epoch': 0.69}

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{'loss': 3.5853, 'grad_norm': 0.2128744274377823, 'learning_rate': 0.00024333196878634163, 'epoch': 0.7}

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{'loss': 3.5886, 'grad_norm': 0.20270884037017822, 'learning_rate': 0.00023635500934422239, 'epoch': 0.71}

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{'loss': 3.5821, 'grad_norm': 0.21049731969833374, 'learning_rate': 0.00019603537011569566, 'epoch': 0.74}

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                                                      {'loss': 3.5768, 'grad_norm': 0.21626333892345428, 'learning_rate': 0.0001928020308484042, 'epoch': 0.74}


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                                                      {'loss': 3.5801, 'grad_norm': 0.2008773386478424, 'learning_rate': 0.00018958919743235897, 'epoch': 0.74}


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{'loss': 3.5614, 'grad_norm': 0.20186598598957062, 'learning_rate': 0.00016769136599599017, 'epoch': 0.76}

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{'loss': 3.5641, 'grad_norm': 0.20630207657814026, 'learning_rate': 0.0001646501820129766, 'epoch': 0.76}

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                                                      {'loss': 3.5589, 'grad_norm': 0.20910252630710602, 'learning_rate': 0.00016163138305256598, 'epoch': 0.76}

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{'loss': 3.5692, 'grad_norm': 0.2093537300825119, 'learning_rate': 0.0001527113038415231, 'epoch': 0.77}

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{'loss': 3.5529, 'grad_norm': 0.20978114008903503, 'learning_rate': 0.0001327181448103661, 'epoch': 0.79}

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                                                      {'loss': 3.557, 'grad_norm': 0.20549732446670532, 'learning_rate': 0.00012995854245163207, 'epoch': 0.79}

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{'loss': 3.5578, 'grad_norm': 0.20274990797042847, 'learning_rate': 0.00011134305278348312, 'epoch': 0.81}

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{'loss': 3.5518, 'grad_norm': 0.21432042121887207, 'learning_rate': 0.00010625520936593375, 'epoch': 0.81}

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{'loss': 3.5509, 'grad_norm': 0.21237409114837646, 'learning_rate': 9.639624318158335e-05, 'epoch': 0.82}

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{'loss': 3.5479, 'grad_norm': 0.20339708030223846, 'learning_rate': 9.399844741560781e-05, 'epoch': 0.82}

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{'loss': 3.5417, 'grad_norm': 0.20382283627986908, 'learning_rate': 9.162775276448015e-05, 'epoch': 0.82}

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                                                      {'loss': 3.5467, 'grad_norm': 0.19913846254348755, 'learning_rate': 7.153655656890773e-05, 'epoch': 0.84}

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{'loss': 3.5363, 'grad_norm': 0.2000787854194641, 'learning_rate': 6.738272954265156e-05, 'epoch': 0.85}

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{'loss': 3.5363, 'grad_norm': 0.2103968858718872, 'learning_rate': 5.561858464291258e-05, 'epoch': 0.86}

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                                                      {'loss': 3.5354, 'grad_norm': 0.19871465861797333, 'learning_rate': 3.093473849336781e-05, 'epoch': 0.9}


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                                                      {'loss': 3.5364, 'grad_norm': 0.20390182733535767, 'learning_rate': 2.9535819277506203e-05, 'epoch': 0.9}

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{'loss': 3.5362, 'grad_norm': 0.2015979140996933, 'learning_rate': 2.6832284358471516e-05, 'epoch': 0.91}

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{'loss': 3.5359, 'grad_norm': 0.199530690908432, 'learning_rate': 1.7288216615031272e-05, 'epoch': 0.92}

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{'loss': 3.5259, 'grad_norm': 0.197474867105484, 'learning_rate': 1.4238751618640577e-05, 'epoch': 0.93}

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                                                      {'loss': 3.5327, 'grad_norm': 0.198598250746727, 'learning_rate': 1.3287025325307511e-05, 'epoch': 0.93}


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{'loss': 3.5285, 'grad_norm': 0.19704172015190125, 'learning_rate': 1.2367787735873993e-05, 'epoch': 0.94}

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{'loss': 3.5297, 'grad_norm': 0.19298093020915985, 'learning_rate': 5.56604678228706e-06, 'epoch': 0.96}

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                                                       {'loss': 3.5362, 'grad_norm': 0.19582685828208923, 'learning_rate': 2.5143995351817882e-06, 'epoch': 0.97}

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{'loss': 3.5269, 'grad_norm': 0.19379498064517975, 'learning_rate': 1.7625149152127318e-06, 'epoch': 0.98}

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                                                       {'loss': 3.5248, 'grad_norm': 0.1948244571685791, 'learning_rate': 6.580000036264244e-07, 'epoch': 0.99}

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                                                       {'loss': 3.5214, 'grad_norm': 0.19294361770153046, 'learning_rate': 2.7341218649834522e-08, 'epoch': 1.0}

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{'train_runtime': 5904.9238, 'train_samples_per_second': 1852.376, 'train_steps_per_second': 1.809, 'train_loss': 3.915034937113105, '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.