* sanity check ranges in freeze.py
this will catch problems earlier and more clearly.
in my case, it appears that deepspeed zero3 sets layer tensor shapes
to [0], which doesn't play well with automatically inferred ranges.
through a bit of luck, inverting ranges still appears to work correctly.
* simplify chained comparison
Allow in message objects the additional key `weight`, which can be set
to 0 (or 1) to cause that message to be masked out (or left unmasked)
for training (similar to [1]). This is helpful for training the model to be robust and
capable of error recovery upon a bad assistant message.
A missing `weight` key defaults to weight 1, to guarantee downward compatibility.
[1]: https://github.com/mistralai/mistral-finetune
* phi-3 support and perplexity metric
* phi-3 chat template
* metrics updates
* chore: lint
* fix assertion on Tensor
* fix tests since tokenization happens in the metric
* fix perplexity value of shorter passage
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* re-enable DPO for tests in modal ci
* workaround for training args
* don't mixin AxolotlTrainingArguments
* fix mixin order so MRO doesn't result in
TypeError: non-default argument follows default argument error
* use smaller datasets for dpo tests
The current yml code throws an error: ValueError: Please set lora_modules_to_save to [`embed_tokens`, `lm_head`] when using an adapter and changing the special tokens.
I added the required changes to resolve it
The strategy now supports configuring several fields: * The data field holding message arrays * the role and
content fields for each message * role mapping from source to target types
additionally this adds a sample llama3-8b instruct template using the chat template
* include mlflow installation in the colab notebook
Without explicitly installing mlflow the `accelerate launch` command fails.
* update the colab noteboko to use the latest tinyllama config
* Switch to parallel FFD bin packing algorithm.
Add support for packing in a distributed context.
Add packing efficiency estimate back.
* revert changes to distributed code
* chore: lint
* fix config w new params for packing test
* add sample_packing_group_size and sample_packing_bin_size to cfg schema
* fix lamdbda function
* fix sampler/dataloader calculations for packing
---------
Co-authored-by: dsesclei <dave@sescleifer.com>
* Fix llama3 chat_template (the {{eos_token}} leads to an extra <|eot_id|> being added in the last turn). Output now matches official Llama 3 Instruct model
* add tests
* chore: lint
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* add kto support
* test cleanup
* fix outdated comment
* fix llama3 ultra
* chore: lint
* update to use rl_beta instead of dpo_beta
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
