Update results_to_dataframe to use BenchmarkResults class

[AlexeyVatolin]

Changed the results_to_dataframe function to make the example from the documentation work.
Error before

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[32], line 11
      7 models = [mteb.get_model_meta(name) for name in results_eval_mteb_df["full_name"].unique()]
      9 results = mteb.load_results(models=models, tasks=tasks)
---> 11 df = results_to_dataframe(results)

File ~/miniconda3/envs/llm_emb/lib/python3.12/site-packages/mteb/task_selection.py:50, in results_to_dataframe(mteb_results, drop_na, **kwargs)
     42 """Convert the results of the MTEB evaluation to a pandas DataFrame.
     43 
     44 Args:
   (...)
     47     **kwargs: Additional keyword arguments to be passed to the `get_score` method of the `MTEBResults` class.
     48 """
     49 data = []
---> 50 for model_name, revisions in mteb_results.items():
     51     for rev, tasks_results in revisions.items():
     52         for task_result in tasks_results:

File ~/miniconda3/envs/llm_emb/lib/python3.12/site-packages/pydantic/main.py:892, in BaseModel.__getattr__(self, item)
    889     return super().__getattribute__(item)  # Raises AttributeError if appropriate
    890 else:
    891     # this is the current error
--> 892     raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')

AttributeError: 'BenchmarkResults' object has no attribute 'items'

Checklist

• Run tests locally to make sure nothing is broken using make test.
• Run the formatter to format the code using make lint.

[isaac-chung]

Thanks for catching this!