bug: tracker params in happy case can cause exception.

[dushyantbehl]

Describe the bug

A tracker params if not passed even in happy case can cause exception.

(.fms-hf-tuning-venv) ➜  fms-hf-tuning git:(fix-bad-value-error) ✗ accelerate launch \
--main_process_port 1234 \
--config_file /home/schrodinger/workspace/ibm/fms-hf-tuning/fixtures/accelerate_fsdp_defaults.yaml \
--num_processes 2 \
-m tuning.sft_trainer \
--model_name_or_path "Maykeye/TinyLLama-v0" \
--training_data_path "/home/schrodinger/bin/twitter_complaints.json" \
--output_dir /home/schrodinger/bin/output/tiny-llama-ft-multigpu \
--num_train_epochs 5 \
--per_device_train_batch_size 4 \
--gradient_accumulation_steps 4 \
--per_device_eval_batch_size 4 \
--learning_rate 0.000001 \
--use_flash_attn no \
--response_template "\n### Label:" \
--dataset_text_field "output" \
--tracker aim \
--aim_repo /home/schrodinger/bin/aimrepo/ \
--experiment aim-test-distributed-main \
--torch_dtype bfloat16
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/accelerate/utils/launch.py:253: FutureWarning: `fsdp_backward_prefetch_policy` is deprecated and will be removed in version 0.27.0 of 🤗 Accelerate. Use `fsdp_backward_prefetch` instead
  warnings.warn(
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 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.
max_seq_length 4096 exceeds tokenizer.model_max_length             2048, using tokenizer.model_max_length 2048
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 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.
Generating train split: 10400 examples [00:00, 279328.40 examples/s]
max_seq_length 4096 exceeds tokenizer.model_max_length             2048, using tokenizer.model_max_length 2048
Map: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10400/10400 [00:00<00:00, 19288.10 examples/s]
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/transformers/training_args.py:2007: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_token` instead.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:100: FutureWarning: Deprecated argument(s) used in '__init__': dataset_text_field, max_seq_length. Will not be supported from version '1.0.0'.

Deprecated positional argument(s) used in SFTTrainer, please use the SFTConfig to set these arguments instead.
  warnings.warn(message, FutureWarning)
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:280: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:318: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/transformers/training_args.py:2007: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_token` instead.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:100: FutureWarning: Deprecated argument(s) used in '__init__': dataset_text_field, max_seq_length. Will not be supported from version '1.0.0'.

Deprecated positional argument(s) used in SFTTrainer, please use the SFTConfig to set these arguments instead.
  warnings.warn(message, FutureWarning)
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:280: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:318: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.
  warnings.warn(
Map: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10400/10400 [00:00<00:00, 39494.35 examples/s]
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:408: UserWarning: You passed a tokenizer with `padding_side` not equal to `right` to the SFTTrainer. This might lead to some unexpected behaviour due to overflow issues when training a model in half-precision. You might consider adding `tokenizer.padding_side = 'right'` to your code.
  warnings.warn(
/home/schrodinger/.fms-hf-tuning-venv/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:408: UserWarning: You passed a tokenizer with `padding_side` not equal to `right` to the SFTTrainer. This might lead to some unexpected behaviour due to overflow issues when training a model in half-precision. You might consider adding `tokenizer.padding_side = 'right'` to your code.
  warnings.warn(
Exception while saving additional metrics and metadata ValueError('set_params passed to aimstack should be called with a dict of params')

Expected behavior

No error should be thrown.