Fix: Gradient Accumulation issue (#1980)

* feat: support new arg num_items_in_batch

* use kwargs to manage extra unknown kwargs for now

* upgrade against upstream transformers main

* make sure trl is on latest too

* fix for upgraded trl

* fix: handle trl and transformer signature change

* feat: update trl to handle transformer signature

* RewardDataCollatorWithPadding no longer has max_length

* handle updated signature for tokenizer vs processor class

* invert logic for tokenizer vs processor class

* processing_class, not processor class

* also handle processing class in dpo

* handle model name w model card creation

* upgrade transformers and add a loss check test

* fix install of tbparse requirements

* make sure to add tbparse to req

* feat: revert kwarg to positional kwarg to be explicit

---------

Co-authored-by: Wing Lian <wing.lian@gmail.com>

tests/e2e/patched/test_unsloth_integration.py

@@ -1,22 +1,12 @@
 """Test module for checking whether the integration of Unsloth with Hugging Face Transformers is working as expected."""
 import unittest
 
-from axolotl.monkeypatch.unsloth_ import (
-    check_cel_is_patchable,
-    check_self_attn_is_patchable,
-)
+from axolotl.monkeypatch.unsloth_ import check_self_attn_is_patchable
 
 
 class TestUnslothIntegration(unittest.TestCase):
     """Unsloth monkeypatch integration tests."""
 
-    def test_is_cel_patchable(self):
-        # ensures the current version of transformers has loss code that matches our patching code
-        self.assertTrue(
-            check_cel_is_patchable(),
-            "HF transformers loss code has changed and isn't patchable",
-        )
-
     def test_is_self_attn_patchable(self):
         # ensures the current version of transformers has loss code that matches our patching code
         self.assertTrue(