fix: typo spelling grammar (#13212)

* fix: typo spelling grammar

* fix: make fixup

docs/source/main_classes/trainer.rst

@@ -197,7 +197,7 @@ which should make the "stop and resume" style of training as close as possible t
 However, due to various default non-deterministic pytorch settings this might not fully work. If you want full
 determinism please refer to `Controlling sources of randomness
 <https://pytorch.org/docs/stable/notes/randomness.html>`__. As explained in the document, that some of those settings
-that make things determinstic (.e.g., ``torch.backends.cudnn.deterministic``) may slow things down, therefore this
+that make things deterministic (.e.g., ``torch.backends.cudnn.deterministic``) may slow things down, therefore this
 can't be done by default, but you can enable those yourself if needed.
 
 

docs/source/model_doc/deberta_v2.rst

@@ -53,7 +53,7 @@ New in v2:
   transformer layer to better learn the local dependency of input tokens.
 - **Sharing position projection matrix with content projection matrix in attention layer** Based on previous
   experiments, this can save parameters without affecting the performance.
-- **Apply bucket to encode relative postions** The DeBERTa-v2 model uses log bucket to encode relative positions
+- **Apply bucket to encode relative positions** The DeBERTa-v2 model uses log bucket to encode relative positions
   similar to T5.
 - **900M model & 1.5B model** Two additional model sizes are available: 900M and 1.5B, which significantly improves the
   performance of downstream tasks.

docs/source/model_doc/speech_to_text.rst

@@ -42,8 +42,8 @@ features. The :class:`~transformers.Speech2TextProcessor` wraps :class:`~transfo
 predicted token ids.
 
 The feature extractor depends on :obj:`torchaudio` and the tokenizer depends on :obj:`sentencepiece` so be sure to
-install those packages before running the examples. You could either install those as extra speech dependancies with
-``pip install transformers"[speech, sentencepiece]"`` or install the packages seperatly with ``pip install torchaudio
+install those packages before running the examples. You could either install those as extra speech dependencies with
+``pip install transformers"[speech, sentencepiece]"`` or install the packages seperately with ``pip install torchaudio
 sentencepiece``. Also ``torchaudio`` requires the development version of the `libsndfile
 <http://www.mega-nerd.com/libsndfile/>`__ package which can be installed via a system package manager. On Ubuntu it can
 be installed as follows: ``apt install libsndfile1-dev``

docs/source/training.rst

@@ -281,7 +281,7 @@ Fine-tuning in native PyTorch
    frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope;
    picture-in-picture" allowfullscreen></iframe>
 
-You might need to restart your notebook at this stage to free some memory, or excute the following code:
+You might need to restart your notebook at this stage to free some memory, or execute the following code:
 
 .. code-block:: python