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ShareGPT_llama2_68M

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ShareGPT_llama2_68M / log.txt
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DorinSht
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2024-06-05 00:42:33.461959: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-06-05 00:42:33.462196: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-06-05 00:42:33.727223: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-06-05 00:42:34.201012: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-06-05 00:42:40.034107: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
06/05/2024 00:42:58 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 6, distributed training: False, 16-bits training: False
06/05/2024 00:42:58 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
_n_gpu=6,
accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None},
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=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_steps=1000,
eval_strategy=steps,
evaluation_strategy=None,
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=None,
group_by_length=False,
half_precision_backend=auto,
hub_always_push=False,
hub_model_id=DorinSht/ShareGPT_llama2_68M,
hub_private_repo=False,
hub_strategy=checkpoint,
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=0.0001,
length_column_name=length,
load_best_model_at_end=False,
local_rank=0,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=./training_outputs_job_117535_1_05-06_00-42,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=500,
logging_strategy=steps,
lr_scheduler_kwargs={},
lr_scheduler_type=linear,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=None,
mp_parameters=,
neftune_noise_alpha=None,
no_cuda=False,
num_train_epochs=3.0,
optim=adamw_torch,
optim_args=None,
optim_target_modules=None,
output_dir=./training_outputs_job_117535_1_05-06_00-42,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=8,
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=['tensorboard'],
restore_callback_states_from_checkpoint=False,
resume_from_checkpoint=None,
run_name=/home/dshteyma/target_draft_coupling_code/target_draft_training/training_outputs,
save_on_each_node=False,
save_only_model=False,
save_safetensors=True,
save_steps=1000,
save_strategy=steps,
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,
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=0.05,
warmup_steps=0,
weight_decay=0.01,
)
Using custom data configuration default-afe4b27d28cbdcb1
06/05/2024 00:42:59 - INFO - datasets.builder - Using custom data configuration default-afe4b27d28cbdcb1
Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
06/05/2024 00:42:59 - INFO - datasets.info - Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
Overwrite dataset info from restored data version if exists.
06/05/2024 00:42:59 - INFO - datasets.builder - Overwrite dataset info from restored data version if exists.
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:42:59 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
06/05/2024 00:42:59 - INFO - datasets.builder - Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:42:59 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
Using custom data configuration default-afe4b27d28cbdcb1
06/05/2024 00:43:00 - INFO - datasets.builder - Using custom data configuration default-afe4b27d28cbdcb1
Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
Overwrite dataset info from restored data version if exists.
06/05/2024 00:43:00 - INFO - datasets.builder - Overwrite dataset info from restored data version if exists.
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
06/05/2024 00:43:00 - INFO - datasets.builder - Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
Using custom data configuration default-afe4b27d28cbdcb1
06/05/2024 00:43:00 - INFO - datasets.builder - Using custom data configuration default-afe4b27d28cbdcb1
Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset Infos from /home/dshteyma/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json
Overwrite dataset info from restored data version if exists.
06/05/2024 00:43:00 - INFO - datasets.builder - Overwrite dataset info from restored data version if exists.
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
06/05/2024 00:43:00 - INFO - datasets.builder - Found cached dataset json (/home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7)
Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
06/05/2024 00:43:00 - INFO - datasets.info - Loading Dataset info from /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7
[INFO|configuration_utils.py:726] 2024-06-05 00:43:01,226 >> loading configuration file config.json from cache at /home/dshteyma/.cache/huggingface/hub/models--JackFram--llama-68m/snapshots/964a5d77df908b69f8d6476fb70e940425b04cb5/config.json
[INFO|configuration_utils.py:789] 2024-06-05 00:43:01,228 >> Model config LlamaConfig {
"_name_or_path": "JackFram/llama-68m",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 0,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"max_position_embeddings": 2048,
"model_type": "llama",
"num_attention_heads": 12,
"num_hidden_layers": 2,
"num_key_value_heads": 12,
"pad_token_id": 1,
"pretraining_tp": 1,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 10000.0,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.41.0.dev0",
"use_cache": true,
"vocab_size": 32000
}
[INFO|tokenization_utils_base.py:2102] 2024-06-05 00:43:01,386 >> loading file tokenizer.model from cache at /home/dshteyma/.cache/huggingface/hub/models--JackFram--llama-68m/snapshots/964a5d77df908b69f8d6476fb70e940425b04cb5/tokenizer.model
[INFO|tokenization_utils_base.py:2102] 2024-06-05 00:43:01,386 >> loading file tokenizer.json from cache at None
[INFO|tokenization_utils_base.py:2102] 2024-06-05 00:43:01,386 >> loading file added_tokens.json from cache at None
[INFO|tokenization_utils_base.py:2102] 2024-06-05 00:43:01,386 >> loading file special_tokens_map.json from cache at /home/dshteyma/.cache/huggingface/hub/models--JackFram--llama-68m/snapshots/964a5d77df908b69f8d6476fb70e940425b04cb5/special_tokens_map.json
[INFO|tokenization_utils_base.py:2102] 2024-06-05 00:43:01,386 >> loading file tokenizer_config.json from cache at /home/dshteyma/.cache/huggingface/hub/models--JackFram--llama-68m/snapshots/964a5d77df908b69f8d6476fb70e940425b04cb5/tokenizer_config.json
[WARNING|logging.py:329] 2024-06-05 00:43:01,390 >> You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
[WARNING|logging.py:329] 2024-06-05 00:43:01,502 >> You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
[INFO|configuration_utils.py:936] 2024-06-05 00:43:02,135 >> Generate config GenerationConfig {
"bos_token_id": 0,
"eos_token_id": 2,
"pad_token_id": 1
}
06/05/2024 00:43:03 - INFO - __main__ - Training new model from scratch - Total size=64.88M params
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-988d048fea8d2473.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-988d048fea8d2473.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-4e281c930893bca9.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-4e281c930893bca9.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-3fe350bccdda6078.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-3fe350bccdda6078.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-35d09b588a0c62b9.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-35d09b588a0c62b9.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-4e5279ee31a5d8d3.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-4e5279ee31a5d8d3.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-63d56456928edd43.arrow
06/05/2024 00:43:03 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-63d56456928edd43.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-6a784a78d9818240.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-6a784a78d9818240.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-46540f58a00a92bf.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-46540f58a00a92bf.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-73605724efaea9d2.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-73605724efaea9d2.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-83d3df87e1b82021.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-83d3df87e1b82021.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-efdbb02491aa6344.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-efdbb02491aa6344.arrow
Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-0cf2ae38fef927f3.arrow
06/05/2024 00:43:04 - INFO - datasets.arrow_dataset - Loading cached processed dataset at /home/dshteyma/.cache/huggingface/datasets/json/default-afe4b27d28cbdcb1/0.0.0/c8d2d9508a2a2067ab02cd118834ecef34c3700d143b31835ec4235bf10109f7/cache-0cf2ae38fef927f3.arrow
06/05/2024 00:43:04 - 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|trainer.py:2068] 2024-06-05 00:43:05,738 >> ***** Running training *****
[INFO|trainer.py:2069] 2024-06-05 00:43:05,738 >> Num examples = 90,745
[INFO|trainer.py:2070] 2024-06-05 00:43:05,738 >> Num Epochs = 3
[INFO|trainer.py:2071] 2024-06-05 00:43:05,738 >> Instantaneous batch size per device = 4
[INFO|trainer.py:2073] 2024-06-05 00:43:05,738 >> Training with DataParallel so batch size has been adjusted to: 24
[INFO|trainer.py:2074] 2024-06-05 00:43:05,738 >> Total train batch size (w. parallel, distributed & accumulation) = 24
[INFO|trainer.py:2075] 2024-06-05 00:43:05,738 >> Gradient Accumulation steps = 1
[INFO|trainer.py:2076] 2024-06-05 00:43:05,738 >> Total optimization steps = 11,346
[INFO|trainer.py:2077] 2024-06-05 00:43:05,738 >> Number of trainable parameters = 68,030,208
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warnings.warn('Was asked to gather along dimension 0, but all '
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[INFO|trainer.py:3664] 2024-06-05 00:59:54,007 >> Num examples = 1840
[INFO|trainer.py:3667] 2024-06-05 00:59:54,007 >> Batch size = 48
{'loss': 5.1118, 'grad_norm': 0.8546391725540161, 'learning_rate': 8.816009873931059e-05, 'epoch': 0.13}
{'loss': 3.406, 'grad_norm': 0.8593688607215881, 'learning_rate': 9.59831475011252e-05, 'epoch': 0.26}
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[INFO|trainer.py:3353] 2024-06-05 01:01:07,874 >> Saving model checkpoint to ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000
[INFO|configuration_utils.py:471] 2024-06-05 01:01:07,888 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000/config.json
[INFO|configuration_utils.py:705] 2024-06-05 01:01:07,894 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000/generation_config.json
[INFO|modeling_utils.py:2592] 2024-06-05 01:01:08,771 >> Model weights saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000/model.safetensors
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:01:08,785 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:01:08,789 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-1000/special_tokens_map.json
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:01:11,153 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:01:11,157 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/special_tokens_map.json
/home/dshteyma/miniconda3/lib/python3.9/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
warnings.warn('Was asked to gather along dimension 0, but all '
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[33:59<2:30:41, 1.04it/s] 17%|█▋ | 1982/11346 [34:00<2:30:36, 1.04it/s] 17%|█▋ | 1983/11346 [34:01<2:30:36, 1.04it/s] 17%|█▋ | 1984/11346 [34:01<2:30:36, 1.04it/s] 17%|█▋ | 1985/11346 [34:02<2:30:32, 1.04it/s] 18%|█▊ | 1986/11346 [34:03<2:30:34, 1.04it/s] 18%|█▊ | 1987/11346 [34:04<2:30:29, 1.04it/s] 18%|█▊ | 1988/11346 [34:05<2:30:29, 1.04it/s] 18%|█▊ | 1989/11346 [34:06<2:30:33, 1.04it/s] 18%|█▊ | 1990/11346 [34:07<2:30:36, 1.04it/s] 18%|█▊ | 1991/11346 [34:08<2:30:37, 1.04it/s] 18%|█▊ | 1992/11346 [34:09<2:30:35, 1.04it/s] 18%|█▊ | 1993/11346 [34:10<2:30:42, 1.03it/s] 18%|█▊ | 1994/11346 [34:11<2:30:38, 1.03it/s] 18%|█▊ | 1995/11346 [34:12<2:30:32, 1.04it/s] 18%|█▊ | 1996/11346 [34:13<2:30:23, 1.04it/s] 18%|█▊ | 1997/11346 [34:14<2:30:21, 1.04it/s] 18%|█▊ | 1998/11346 [34:15<2:30:18, 1.04it/s] 18%|█▊ | 1999/11346 [34:16<2:30:18, 1.04it/s] 18%|█▊ | 2000/11346 [34:17<2:30:19, 1.04it/s] 18%|█▊ | 2000/11346 [34:17<2:30:19, 1.04it/s][INFO|trainer.py:3662] 2024-06-05 01:17:23,214 >> ***** Running Evaluation *****
[INFO|trainer.py:3664] 2024-06-05 01:17:23,214 >> Num examples = 1840
[INFO|trainer.py:3667] 2024-06-05 01:17:23,214 >> Batch size = 48
{'eval_loss': 3.23445987701416, 'eval_accuracy': 0.5035306174465283, 'eval_runtime': 73.8676, 'eval_samples_per_second': 24.909, 'eval_steps_per_second': 0.528, 'epoch': 0.26}
{'loss': 3.0005, 'grad_norm': 0.9617258906364441, 'learning_rate': 9.134314230431938e-05, 'epoch': 0.4}
{'loss': 2.8119, 'grad_norm': 0.8953185677528381, 'learning_rate': 8.670313710751356e-05, 'epoch': 0.53}
0%| | 0/39 [00:00<?, ?it/s]
5%|▌ | 2/39 [00:01<00:27, 1.36it/s]
8%|▊ | 3/39 [00:02<00:37, 1.04s/it]
10%|█ | 4/39 [00:04<00:41, 1.20s/it]
13%|█▎ | 5/39 [00:05<00:43, 1.29s/it]
15%|█▌ | 6/39 [00:07<00:44, 1.35s/it]
18%|█▊ | 7/39 [00:08<00:44, 1.39s/it]
21%|██ | 8/39 [00:10<00:43, 1.41s/it]
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[INFO|trainer.py:3353] 2024-06-05 01:18:36,124 >> Saving model checkpoint to ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000
[INFO|configuration_utils.py:471] 2024-06-05 01:18:36,137 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000/config.json
[INFO|configuration_utils.py:705] 2024-06-05 01:18:36,142 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000/generation_config.json
[INFO|modeling_utils.py:2592] 2024-06-05 01:18:37,058 >> Model weights saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000/model.safetensors
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:18:37,072 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:18:37,077 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-2000/special_tokens_map.json
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:18:39,363 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:18:39,367 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/special_tokens_map.json
/home/dshteyma/miniconda3/lib/python3.9/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
warnings.warn('Was asked to gather along dimension 0, but all '
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[INFO|trainer.py:3664] 2024-06-05 01:34:53,017 >> Num examples = 1840
[INFO|trainer.py:3667] 2024-06-05 01:34:53,017 >> Batch size = 48
{'eval_loss': 2.821384906768799, 'eval_accuracy': 0.5365118094348038, 'eval_runtime': 72.909, 'eval_samples_per_second': 25.237, 'eval_steps_per_second': 0.535, 'epoch': 0.53}
{'loss': 2.686, 'grad_norm': 1.4154396057128906, 'learning_rate': 8.206313191070773e-05, 'epoch': 0.66}
{'loss': 2.607, 'grad_norm': 1.821349024772644, 'learning_rate': 7.742312671390191e-05, 'epoch': 0.79}
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[INFO|trainer.py:3353] 2024-06-05 01:36:06,445 >> Saving model checkpoint to ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000
[INFO|configuration_utils.py:471] 2024-06-05 01:36:06,461 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000/config.json
[INFO|configuration_utils.py:705] 2024-06-05 01:36:06,467 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000/generation_config.json
[INFO|modeling_utils.py:2592] 2024-06-05 01:36:07,371 >> Model weights saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000/model.safetensors
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:36:07,385 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:36:07,389 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-3000/special_tokens_map.json
[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:36:09,981 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/tokenizer_config.json
[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:36:09,986 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/special_tokens_map.json
/home/dshteyma/miniconda3/lib/python3.9/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
warnings.warn('Was asked to gather along dimension 0, but all '