diff --git "a/log.txt" "b/log.txt"
deleted file mode 100644--- "a/log.txt"
+++ /dev/null
@@ -1,480 +0,0 @@
-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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-[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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 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}
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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 '
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 35%|███▌      | 4000/11346 [1:09:18<2:00:20,  1.02it/s][INFO|trainer.py:3662] 2024-06-05 01:52:24,242 >> ***** Running Evaluation *****
-[INFO|trainer.py:3664] 2024-06-05 01:52:24,242 >>   Num examples = 1840
-[INFO|trainer.py:3667] 2024-06-05 01:52:24,242 >>   Batch size = 48
-{'eval_loss': 2.657219886779785, 'eval_accuracy': 0.5497897240925214, 'eval_runtime': 73.4297, 'eval_samples_per_second': 25.058, 'eval_steps_per_second': 0.531, 'epoch': 0.79}
-{'loss': 2.5642, 'grad_norm': 2.0297396183013916, 'learning_rate': 7.278312151709609e-05, 'epoch': 0.93}
-{'loss': 2.4734, 'grad_norm': 2.8318285942077637, 'learning_rate': 6.814311632029027e-05, 'epoch': 1.06}
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                                               [INFO|trainer.py:3353] 2024-06-05 01:53:37,708 >> Saving model checkpoint to ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000
-[INFO|configuration_utils.py:471] 2024-06-05 01:53:37,724 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000/config.json
-[INFO|configuration_utils.py:705] 2024-06-05 01:53:37,729 >> Configuration saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000/generation_config.json
-[INFO|modeling_utils.py:2592] 2024-06-05 01:53:38,645 >> Model weights saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000/model.safetensors
-[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:53:38,658 >> tokenizer config file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000/tokenizer_config.json
-[INFO|tokenization_utils_base.py:2512] 2024-06-05 01:53:38,663 >> Special tokens file saved in ./training_outputs_job_117535_1_05-06_00-42/checkpoint-4000/special_tokens_map.json
-[INFO|tokenization_utils_base.py:2503] 2024-06-05 01:53:40,961 >> 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 01:53:40,966 >> 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 '