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WARNING:__main__:Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False
INFO:__main__:Training/evaluation parameters TrainingArguments(
_n_gpu=1,
accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False},
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=False,
batch_eval_metrics=False,
bf16=False,
bf16_full_eval=False,
data_seed=None,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_persistent_workers=False,
dataloader_pin_memory=True,
dataloader_prefetch_factor=None,
ddp_backend=None,
ddp_broadcast_buffers=None,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
ddp_timeout=1800,
debug=[],
deepspeed=None,
disable_tqdm=False,
dispatch_batches=None,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=None,
eval_delay=0,
eval_do_concat_batches=True,
eval_on_start=False,
eval_steps=None,
eval_strategy=IntervalStrategy.EPOCH,
eval_use_gather_object=False,
evaluation_strategy=epoch,
fp16=False,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
fsdp=[],
fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False},
fsdp_min_num_params=0,
fsdp_transformer_layer_cls_to_wrap=None,
full_determinism=False,
gradient_accumulation_steps=1,
gradient_checkpointing=False,
gradient_checkpointing_kwargs=None,
greater_is_better=False,
group_by_length=False,
half_precision_backend=auto,
hub_always_push=False,
hub_model_id=None,
hub_private_repo=False,
hub_strategy=HubStrategy.EVERY_SAVE,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
include_inputs_for_metrics=False,
include_num_input_tokens_seen=False,
include_tokens_per_second=False,
jit_mode_eval=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=5e-05,
length_column_name=length,
load_best_model_at_end=True,
local_rank=0,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=/home/iais_marenpielka/Bouthaina/clss_all_aragpt2-large/runs/Sep21_19-26-22_lmgpu-node-05,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=500,
logging_strategy=IntervalStrategy.EPOCH,
lr_scheduler_kwargs={},
lr_scheduler_type=SchedulerType.LINEAR,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=loss,
mp_parameters=,
neftune_noise_alpha=None,
no_cuda=False,
num_train_epochs=20.0,
optim=OptimizerNames.ADAMW_TORCH,
optim_args=None,
optim_target_modules=None,
output_dir=/home/iais_marenpielka/Bouthaina/clss_all_aragpt2-large,
overwrite_output_dir=False,
past_index=-1,
per_device_eval_batch_size=4,
per_device_train_batch_size=4,
prediction_loss_only=False,
push_to_hub=True,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
ray_scope=last,
remove_unused_columns=True,
report_to=[],
restore_callback_states_from_checkpoint=False,
resume_from_checkpoint=None,
run_name=/home/iais_marenpielka/Bouthaina/clss_all_aragpt2-large,
save_on_each_node=False,
save_only_model=False,
save_safetensors=True,
save_steps=500,
save_strategy=IntervalStrategy.EPOCH,
save_total_limit=None,
seed=42,
skip_memory_metrics=True,
split_batches=None,
tf32=None,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
torch_empty_cache_steps=None,
torchdynamo=None,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_cpu=False,
use_ipex=False,
use_legacy_prediction_loop=False,
use_mps_device=False,
warmup_ratio=0.0,
warmup_steps=500,
weight_decay=0.0,
)
INFO:datasets.builder:Using custom data configuration default-d16f90cf72c9c046
INFO:datasets.info:Loading Dataset Infos from /home/iais_marenpielka/Bouthaina/miniconda3/lib/python3.12/site-packages/datasets/packaged_modules/text
INFO:datasets.builder:Generating dataset text (/home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101)
INFO:datasets.builder:Downloading and preparing dataset text/default to /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101...
INFO:datasets.download.download_manager:Downloading took 0.0 min
INFO:datasets.download.download_manager:Checksum Computation took 0.0 min
INFO:datasets.builder:Generating train split
INFO:datasets.builder:Generating validation split
INFO:datasets.utils.info_utils:Unable to verify splits sizes.
INFO:datasets.builder:Dataset text downloaded and prepared to /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101. Subsequent calls will reuse this data.
INFO:datasets.arrow_dataset:Caching processed dataset at /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101/cache-7c7a4ce4606d72ba.arrow
INFO:datasets.arrow_dataset:Caching processed dataset at /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101/cache-f857889408f331fc.arrow
WARNING:__main__:The tokenizer picked seems to have a very large `model_max_length` (1000000000000000019884624838656). Using block_size=1024 instead. You can change that default value by passing --block_size xxx.
INFO:datasets.arrow_dataset:Caching processed dataset at /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101/cache-c506adc684dad231.arrow
INFO:datasets.arrow_dataset:Caching processed dataset at /home/iais_marenpielka/.cache/huggingface/datasets/text/default-d16f90cf72c9c046/0.0.0/96636a050ef51804b84abbfd4f4ad440e01153c24b86293eb5c3b300a41f9101/cache-88ed0420274727ab.arrow
WARNING:accelerate.utils.other:Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
INFO:root:Epoch 1.0: Train Loss = None, Eval Loss = None
INFO:absl:Using default tokenizer.
INFO:root:Epoch 2.0: Train Loss = 0.0822, Eval Loss = 0.08718258142471313
INFO:absl:Using default tokenizer.
INFO:root:Epoch 3.0: Train Loss = 0.0466, Eval Loss = 0.10128764063119888
INFO:absl:Using default tokenizer.
INFO:root:Epoch 4.0: Train Loss = 0.04, Eval Loss = 0.09248281270265579
INFO:absl:Using default tokenizer.
INFO:root:Epoch 5.0: Train Loss = 0.0334, Eval Loss = 0.062421105802059174
INFO:absl:Using default tokenizer.
INFO:root:Epoch 6.0: Train Loss = 0.0274, Eval Loss = 0.07504618912935257
INFO:absl:Using default tokenizer.
INFO:root:Epoch 7.0: Train Loss = 0.023, Eval Loss = 0.06978417932987213
INFO:absl:Using default tokenizer.
INFO:root:Epoch 8.0: Train Loss = 0.0199, Eval Loss = 0.06847791373729706
INFO:absl:Using default tokenizer.
INFO:root:Epoch 9.0: Train Loss = 0.0179, Eval Loss = 0.0721321851015091
INFO:absl:Using default tokenizer.
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