kto_lora2_output_new
This is a LoRA adapter trained with KTO on the werewolf_kto dataset.
This is a re-trained / updated version of the earlier kto_lora2_output run
(trained for more steps, see trainer_state.json).
Base model
The adapter was trained on top of an internal SFT-merged base model.
In adapter_config.json, base_model_name_or_path is set to the placeholder
string werewolf_sft2_merged, which is not a public Hugging Face repo id.
To load this adapter you must:
- Obtain the matching base model
werewolf_sft2_merged from the team
(this is the SFT-merged checkpoint used during KTO training).
- Either place it at a local path and point
base_model_name_or_path to that
path, or pass the base model explicitly when calling
PeftModel.from_pretrained(base_model, adapter_path).
Intended uses & limitations
Internal use for the werewolf agent project. Not intended for general-purpose
deployment.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3.0
Framework versions
- PEFT 0.18.1
- Transformers 5.6.0
- Pytorch 2.12.0+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2
