v0.12.0

Changed

• Python bumped to >= 3.10, tests up to 3.13
• Bumped datasets to >= 3.0, < 3.2
• Bumped lightning to < 2.6
• Remove hard dependency on sentencepiece. Users can still install it if the tokenizer they use
  needs it, but their release policy is too brittle to allow them to block us, especially since it's
  only a quality of life dependency for us.
• Bumped torch to < 2.7
• Bumped tokenizers to < 0.22
• Bumped transformers to allow < 5.0, skipping versions from 4.41 to 4.43

Full Changelog: v0.11.0...v0.12.0

v0.11.0

Changed

• Several dumps of environments added to the output dir of transformer training to help with reproducibility and bug reporting.

Full Changelog: v0.10.0...v0.11.0

v0.10.0

Changed

• Bumped minimal (Pytorch) Lightning version to 2.0.0
• Pytorch compatibility changed to >= 2.0, < 2.4
• 🤗 datasets compatibility changed to >= 2.18, < 2.20
• Added support for the new lightning precision plugins.

Full Changelog: v0.9.0...v0.10.0

v0.9.0

Fixed

• Training a m2m100 model on a language (code) not originally included in its tokenizer now works.

Changed

• Pytorch compatibility changed to >= 2.0, < 2.3
• 🤗 datasets compatibility changed to >= 2.18, < 2.19

Full Changelog: v0.8.0...v0.9.0

v0.8.0

Fixed

• Fixed multiple save when using step-save-period in conjunction with bach accumulation (close #30)

Changed

• Maximum Pyorch compatibility bumped to 2.1
• max_steps and max_epochs can now be set in the tuning config. Setting them via command line
  options is deprecated and will be removed in a future version.

v0.7.3 — Bug Fix

Fixed

• Behaviour when asking for denoising in mBART with a model that has no mask token.

v0.7.2 — Now with a doc??!?

Fixed

• In mBART training, loss scaling now works as it was supposed to.
• We have a documentation now! Check it out at https://zeldarose.readthedocs.io, it will get
  better over time (hopefully!).

v0.7.1 Bug fix

Fixed

• Translate loss logging is not always zero anymore.

Now with mBART translations!

The main highlight of this release is the addition of mBART training as a task, so far slightly different from the original one, but similar enough to work in our tests.

Added

• The --tf32-mode option allows to select the level of NVidia Ampère matmul otpimisations.
• The --seed option allows to fix a random seed.
• The mbart task allows training general seq2seq and translation models.
• A zeldarose command that serves as entry point for both tokenizer and transformer training.

Changed

• BREAKING --use-fp16 has been replaced by --precision, which allows to also use fp64 and
  bfloat. Previous behaviour can be emulated with --precision 16.
• Remove the GPU stats logging from the profile mode since Lightning stopped supporting it
• Switched TOML library from toml to
  tomli
• BREAKING Bumped the min version of several dependency
  • pytorch-lightning >= 1.8.0
  • torch >= 1.12
• Bumped max version of several dependency
  • datasets < 2.10
  • pytorch-lightning < 1.9
  • tokenizers < 0.14

v0.6.0 — Dependencies compatibilities

This one to fix compatibilities issues with our dependencies. Bumps minimal versions and add upper version limits.

Changed

• Bumped torchmetrics minimal version to 0.9
• Bumped datasets minimal version to 2.4
• Bumped torch max version to 1.12

Fixed

• Dataset fingerprinting/caching issues #31

Full Changelog: v0.5.0...v0.6.0