Retrain models with updated dependencies

[x-tabdeveloping]

How to reproduce the behaviour

Using newer versions of transformers (4.36.2) and spacy-transformers (1.3.5) results in warnings indicating that the pipeline should probably be retrained on newer versions of these libraries.

/home/au689890/anaconda3/envs/seb/lib/python3.9/site-packages/spacy/util.py:910: UserWarning: [W095] Model 'da_dacy_small_trf' (0.2.0) was trained with spaCy v3.5.2 and may not be 100% compat
ible with the current version (3.7.4). If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current spaCy version. For more detai
ls and available updates, run: python -m spacy validate
  warnings.warn(warn_msg)
/home/au689890/anaconda3/envs/seb/lib/python3.9/site-packages/spacy_transformers/layers/hf_shim.py:137: UserWarning: Error loading saved torch state_dict with strict=True, likely due to diffe
rences between 'transformers' versions. Attempting to load with strict=False as a fallback...

If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current 'transformers' and 'spacy-transformers' versions. For more details a
nd available updates, run: python -m spacy validate
  warnings.warn(warn_msg)

Your Environment

• DaCy Version Used: 2.7.7
• Operating System: Ubuntu 20.04.6 LTS
• Python Version Used: 3.9.18
• spaCy Version Used: 3.7.4

[KennethEnevoldsen]

Thanks @x-tabdeveloping, I don't believe this is a bug, but I agree that we would love to retrain the pipeline

[x-tabdeveloping]

Yeah I just didn't know which template to choose, sorry about that :D

[KennethEnevoldsen]

No problem, probably won't get to this at least before after the summer holidays

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