Signed-off-by: YAO Matrix <matrix.yao@intel.com>

FIX Transformers VLM architecture changes

Follow up to huggingface#2554
See discussion in huggingface/transformers#38627

To quote:

> transformers PR #37033 re-arranges the way visual language models are
built by moving the LM head from the language model to the top-level
VLM (among other things).

A consequence of this is that the keys in the PEFT state_dict now also
follow the new architecture. This means that:

1. If a PEFT checkpoint was saved with the old architecture but is
   loaded with the new architecture, loading fails.
2. If a PEFT checkpoint was saved with the new architecture but is
   loaded with the old architecture, loading fails.

1. can be addressed by making use of the newly added
_checkpoint_conversion_mapping attribute for models with the new
architecture. In transformers, this is used to map old model state_dicts
to the new state_dict format. In PEFT, with some fiddling, we can use
the same mapping to make old PEFT state_dicts compatible with the new
architecture (backwards compatibility).

However, 2. is not easily addressed. We would need a reverse mapping for
this. This could be easily derived from _checkpoint_conversion_mapping,
but since this attribute doesn't exist on old models, we cannot do that.
Therefore, new checkpoints created with PEFT on these models won't load
successfully when users use old transformers (forward compatibility).

These cases are covered by the added unit tests, which means that the
test covering case 2 are marked as xfail.

If we could reliably detect that we are in case 2, we could warn the
user and advise them to upgrade transformers, but I don't know if it's
possible to figure this out.

We also allow users to pass their own key_mapping to from_pretrained and
load_adapter, though the documentation advises against it. This argument
could theoretically be used as a workaround in case there is indeed an
issue with prompt learning state_dicts.

Apart from these changes, I also made a small change to account for
huggingface/transformers#38017 (comment).

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

This change updates all results with their respective number of
parameters (trained + absolute) and adds the newly introduced
full-finetuning.

In addition to these results there was also an issue with the
Makefile as it didn't consider the possibility of having experiments
that don't have an adapter config (e.g., full fine-tuning).

Signed-off-by: YAO Matrix <matrix.yao@intel.com>