docs: Add DeepSeek entry in Changelog and bump Nemo commit

[yfw]

What does this PR do ?

Add DeepSeek entry in Changelog and bump Nemo commit.

Changelog

• Please update the CHANGELOG.md under next version with high level changes in this PR.

Usage

• You can potentially add a usage example below

/usr/bin/python /opt/NeMo-Aligner/examples/nlp/gpt/train_gpt_sft.py \
   trainer.precision=bf16 \
   trainer.num_nodes=64 \
   trainer.devices=8 \
   trainer.sft.max_steps=${MAX_STEPS} \
   trainer.sft.limit_val_batches=null \
   trainer.sft.val_check_interval=100 \
   model.megatron_amp_O2=True \
   model.restore_from_path=${MODEL} \
   model.optim.lr=5e-6 \
   model.optim.name=mcore_distributed_optim \
   model.optim.sched.min_lr=5e-7 \
   model.optim.sched.warmup_steps=50 \
   model.optim.sched.constant_steps=0 \
   ++model.optim.eps=1e-5 \
   ++model.optim.sched.max_steps=${MAX_STEPS} \
   model.tensor_model_parallel_size=${TP_SIZE} \
   model.pipeline_model_parallel_size=${PP_SIZE} \
   model.data.chat=False \
   model.data.num_workers=0 \
   model.data.train_ds.micro_batch_size=1 \
   model.data.train_ds.global_batch_size=128 \
   model.data.train_ds.max_seq_length=2048 \
   model.data.train_ds.file_path=${TRAIN_DS} \
   model.data.validation_ds.micro_batch_size=1 \
   model.data.validation_ds.global_batch_size=128 \
   model.data.validation_ds.file_path=${VALID_DS} \
   model.data.validation_ds.max_seq_length=2048 \
   exp_manager.create_wandb_logger=True \
   exp_manager.explicit_log_dir=${OUTPUT_DIR} \
   exp_manager.wandb_logger_kwargs.project=debug-nemo2 \
   exp_manager.wandb_logger_kwargs.name=sft_deepseekv3-dfw-adam_eps1e-5 \
   exp_manager.checkpoint_callback_params.save_nemo_on_train_end=False \
   exp_manager.resume_if_exists=False \
   exp_manager.resume_ignore_no_checkpoint=True \
   exp_manager.create_checkpoint_callback=True \
   exp_manager.checkpoint_callback_params.monitor=val_loss \
   ++model.num_layers_in_first_pipeline_stage=${PP_FIRST} \
   ++model.num_layers_in_last_pipeline_stage=${PP_LAST} \
   ++model.expert_model_parallel_size=${EP_SIZE} \
   ++model.transformer_engine=True \
   ++model.dist_ckpt_load_strictness=log_all \
   ++model.name=decoder_block_gpt \
   ++model.moe_layer_freq=[0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] \
   ++model.seq_length=2048

Before your PR is "Ready for review"

Pre checks:

• Make sure you read and followed Contributor guidelines
• Did you write any new necessary tests?
• Did you add or update any necessary documentation? Make sure to also update the NeMo Framework User Guide which contains the tutorials

Checklist when contributing a new algorithm

• Does the trainer resume and restore model state all states?
• Does the trainer support all parallelism techniques(PP, TP, DP)?
• Does the trainer support max_steps=-1 and validation?
• Does the trainer only call APIs defined in alignable_interface.py?
• Does the trainer have proper logging?

Additional Information

• Related to # (issue)

[jgerh]

Reviewed the revisions in CHANGELOG.md. No copyedits needed. Approved.