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Model: the-jb/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff Source: Original Platform
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609
.hydra/config.yaml
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609
.hydra/config.yaml
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|||||||
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model:
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||||||
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model_args:
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||||||
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pretrained_model_name_or_path: open-unlearning/tofu_Llama-3.2-3B-Instruct_full
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||||||
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attn_implementation: flash_attention_2
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||||||
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torch_dtype: bfloat16
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||||||
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tokenizer_args:
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||||||
|
pretrained_model_name_or_path: meta-llama/Llama-3.2-3B-Instruct
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||||||
|
template_args:
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||||||
|
apply_chat_template: true
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||||||
|
system_prompt: You are a helpful assistant.
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||||||
|
system_prompt_with_special_tokens: '<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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||||||
|
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||||||
|
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||||||
|
You are a helpful assistant.<|eot_id|>'
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||||||
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user_start_tag: '<|start_header_id|>user<|end_header_id|>
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||||||
|
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||||||
|
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||||||
|
'
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||||||
|
user_end_tag: <|eot_id|>
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||||||
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asst_start_tag: '<|start_header_id|>assistant<|end_header_id|>
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||||||
|
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||||||
|
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||||||
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'
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asst_end_tag: <|eot_id|>
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date_string: 10 Apr 2025
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trainer:
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||||||
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handler: GradDiff
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||||||
|
args:
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||||||
|
per_device_train_batch_size: 4
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||||||
|
per_device_eval_batch_size: 16
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|
gradient_accumulation_steps: 4
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||||||
|
learning_rate: 1.0e-05
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||||||
|
bf16: true
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||||||
|
bf16_full_eval: true
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logging_steps: 5
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|
output_dir: ${paths.output_dir}
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logging_dir: ${trainer.args.output_dir}/logs
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||||||
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report_to: tensorboard
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||||||
|
ddp_find_unused_parameters: true
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||||||
|
gradient_checkpointing: true
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||||||
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optim: paged_adamw_32bit
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||||||
|
save_strategy: 'no'
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||||||
|
save_only_model: true
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||||||
|
weight_decay: 0.01
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||||||
|
do_train: true
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||||||
|
do_eval: true
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||||||
|
eval_on_start: true
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||||||
|
eval_strategy: epoch
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||||||
|
num_train_epochs: 10
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||||||
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seed: 0
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||||||
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warmup_epochs: 1.0
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||||||
|
remove_unused_columns: false
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||||||
|
method_args:
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||||||
|
gamma: 1.0
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||||||
|
alpha: 1.0
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||||||
|
retain_loss_type: NLL
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||||||
|
data:
|
||||||
|
forget:
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||||||
|
TOFU_QA_forget:
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||||||
|
handler: QADataset
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||||||
|
args:
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||||||
|
hf_args:
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||||||
|
name: ${forget_split}
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||||||
|
split: train
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||||||
|
path: locuslab/TOFU
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||||||
|
question_key: question
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||||||
|
answer_key: answer
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||||||
|
max_length: 512
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||||||
|
retain:
|
||||||
|
TOFU_QA_retain:
|
||||||
|
handler: QADataset
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||||||
|
args:
|
||||||
|
hf_args:
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||||||
|
name: ${retain_split}_wo_test
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||||||
|
split: train
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||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
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||||||
|
answer_key: answer
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||||||
|
max_length: 512
|
||||||
|
anchor: forget
|
||||||
|
collator:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
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||||||
|
eval:
|
||||||
|
tofu:
|
||||||
|
metrics:
|
||||||
|
forget_quality:
|
||||||
|
pre_compute:
|
||||||
|
forget_truth_ratio:
|
||||||
|
pre_compute:
|
||||||
|
forget_Q_A_PARA_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget_para:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: paraphrased_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
forget_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: closer_to_1_better
|
||||||
|
access_key: forget
|
||||||
|
reference_logs:
|
||||||
|
retain_model_logs:
|
||||||
|
path: ${eval.tofu.retain_logs_path}
|
||||||
|
include:
|
||||||
|
forget_truth_ratio:
|
||||||
|
access_key: retain
|
||||||
|
handler: ks_test
|
||||||
|
forget_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
forget_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
model_utility:
|
||||||
|
pre_compute:
|
||||||
|
retain_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_eval:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
retain_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_eval:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
retain_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
retain_Q_A_PARA_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_para:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: paraphrased_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
retain_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
ra_Q_A_Prob_normalised:
|
||||||
|
pre_compute:
|
||||||
|
ra_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
ra_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: probability_w_options
|
||||||
|
ra_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
ra_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
ra_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
ra_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
wf_Q_A_Prob_normalised:
|
||||||
|
pre_compute:
|
||||||
|
wf_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
wf_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: probability_w_options
|
||||||
|
wf_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
wf_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
wf_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
wf_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
handler: hm_aggregate
|
||||||
|
privleak:
|
||||||
|
pre_compute:
|
||||||
|
mia_min_k:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
access_key: forget
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
TOFU_QA_holdout:
|
||||||
|
access_key: holdout
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.holdout_split}
|
||||||
|
path: locuslab/TOFU
|
||||||
|
split: train
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
batch_size: 32
|
||||||
|
handler: mia_min_k
|
||||||
|
k: 0.4
|
||||||
|
access_key: forget
|
||||||
|
reference_logs:
|
||||||
|
retain_model_logs:
|
||||||
|
path: ${eval.tofu.retain_logs_path}
|
||||||
|
include:
|
||||||
|
mia_min_k:
|
||||||
|
access_key: retain
|
||||||
|
handler: privleak
|
||||||
|
ref_value: 0.5
|
||||||
|
extraction_strength:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: extraction_strength
|
||||||
|
batch_size: 32
|
||||||
|
handler: TOFUEvaluator
|
||||||
|
output_dir: ${paths.output_dir}
|
||||||
|
overwrite: true
|
||||||
|
forget_split: ${forget_split}
|
||||||
|
holdout_split: ${holdout_split}
|
||||||
|
retain_logs_path: ${retain_logs_path}
|
||||||
|
paths:
|
||||||
|
root_dir: .
|
||||||
|
data_dir: ${paths.root_dir}/data/
|
||||||
|
datasets: ${paths.root_dir}/configs/data/datasets
|
||||||
|
output_dir: ${paths.root_dir}/saves/${mode}/${task_name}
|
||||||
|
work_dir: ${hydra:runtime.cwd}
|
||||||
|
forget_split: forget10
|
||||||
|
retain_split: retain90
|
||||||
|
holdout_split: holdout10
|
||||||
|
retain_logs_path: saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
task_name: tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
mode: unlearn
|
||||||
279
.hydra/hydra.yaml
Normal file
279
.hydra/hydra.yaml
Normal file
@@ -0,0 +1,279 @@
|
|||||||
|
hydra:
|
||||||
|
run:
|
||||||
|
dir: ${paths.output_dir}
|
||||||
|
sweep:
|
||||||
|
dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
|
||||||
|
subdir: ${hydra.job.num}
|
||||||
|
launcher:
|
||||||
|
_target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
|
||||||
|
sweeper:
|
||||||
|
_target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
|
||||||
|
max_batch_size: null
|
||||||
|
params: null
|
||||||
|
help:
|
||||||
|
app_name: ${hydra.job.name}
|
||||||
|
header: '${hydra.help.app_name} is powered by Hydra.
|
||||||
|
|
||||||
|
'
|
||||||
|
footer: 'Powered by Hydra (https://hydra.cc)
|
||||||
|
|
||||||
|
Use --hydra-help to view Hydra specific help
|
||||||
|
|
||||||
|
'
|
||||||
|
template: '${hydra.help.header}
|
||||||
|
|
||||||
|
== Configuration groups ==
|
||||||
|
|
||||||
|
Compose your configuration from those groups (group=option)
|
||||||
|
|
||||||
|
|
||||||
|
$APP_CONFIG_GROUPS
|
||||||
|
|
||||||
|
|
||||||
|
== Config ==
|
||||||
|
|
||||||
|
Override anything in the config (foo.bar=value)
|
||||||
|
|
||||||
|
|
||||||
|
$CONFIG
|
||||||
|
|
||||||
|
|
||||||
|
${hydra.help.footer}
|
||||||
|
|
||||||
|
'
|
||||||
|
hydra_help:
|
||||||
|
template: 'Hydra (${hydra.runtime.version})
|
||||||
|
|
||||||
|
See https://hydra.cc for more info.
|
||||||
|
|
||||||
|
|
||||||
|
== Flags ==
|
||||||
|
|
||||||
|
$FLAGS_HELP
|
||||||
|
|
||||||
|
|
||||||
|
== Configuration groups ==
|
||||||
|
|
||||||
|
Compose your configuration from those groups (For example, append hydra/job_logging=disabled
|
||||||
|
to command line)
|
||||||
|
|
||||||
|
|
||||||
|
$HYDRA_CONFIG_GROUPS
|
||||||
|
|
||||||
|
|
||||||
|
Use ''--cfg hydra'' to Show the Hydra config.
|
||||||
|
|
||||||
|
'
|
||||||
|
hydra_help: ???
|
||||||
|
hydra_logging:
|
||||||
|
version: 1
|
||||||
|
formatters:
|
||||||
|
colorlog:
|
||||||
|
(): colorlog.ColoredFormatter
|
||||||
|
format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
|
||||||
|
handlers:
|
||||||
|
console:
|
||||||
|
class: logging.StreamHandler
|
||||||
|
formatter: colorlog
|
||||||
|
stream: ext://sys.stdout
|
||||||
|
root:
|
||||||
|
level: INFO
|
||||||
|
handlers:
|
||||||
|
- console
|
||||||
|
disable_existing_loggers: false
|
||||||
|
job_logging:
|
||||||
|
version: 1
|
||||||
|
formatters:
|
||||||
|
simple:
|
||||||
|
format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
|
||||||
|
colorlog:
|
||||||
|
(): colorlog.ColoredFormatter
|
||||||
|
format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
|
||||||
|
- %(message)s'
|
||||||
|
log_colors:
|
||||||
|
DEBUG: purple
|
||||||
|
INFO: green
|
||||||
|
WARNING: yellow
|
||||||
|
ERROR: red
|
||||||
|
CRITICAL: red
|
||||||
|
handlers:
|
||||||
|
console:
|
||||||
|
class: logging.StreamHandler
|
||||||
|
formatter: colorlog
|
||||||
|
stream: ext://sys.stdout
|
||||||
|
file:
|
||||||
|
class: logging.FileHandler
|
||||||
|
formatter: simple
|
||||||
|
filename: ${hydra.runtime.output_dir}/${trainer.handler}.log
|
||||||
|
root:
|
||||||
|
level: INFO
|
||||||
|
handlers:
|
||||||
|
- console
|
||||||
|
- file
|
||||||
|
disable_existing_loggers: false
|
||||||
|
env: {}
|
||||||
|
mode: RUN
|
||||||
|
searchpath: []
|
||||||
|
callbacks: {}
|
||||||
|
output_subdir: .hydra
|
||||||
|
overrides:
|
||||||
|
hydra:
|
||||||
|
- hydra.mode=RUN
|
||||||
|
task:
|
||||||
|
- experiment=unlearn/tofu/default.yaml
|
||||||
|
- trainer=GradDiff
|
||||||
|
- task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- model=Llama-3.2-3B-Instruct
|
||||||
|
- forget_split=forget10
|
||||||
|
- retain_split=retain90
|
||||||
|
- model.model_args.pretrained_model_name_or_path=open-unlearning/tofu_Llama-3.2-3B-Instruct_full
|
||||||
|
- retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
- trainer.args.per_device_train_batch_size=4
|
||||||
|
- trainer.args.gradient_accumulation_steps=4
|
||||||
|
- trainer.args.ddp_find_unused_parameters=true
|
||||||
|
- trainer.args.gradient_checkpointing=true
|
||||||
|
job:
|
||||||
|
name: train
|
||||||
|
chdir: null
|
||||||
|
override_dirname: experiment=unlearn/tofu/default.yaml,forget_split=forget10,model.model_args.pretrained_model_name_or_path=open-unlearning/tofu_Llama-3.2-3B-Instruct_full,model=Llama-3.2-3B-Instruct,retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json,retain_split=retain90,task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff,trainer.args.ddp_find_unused_parameters=true,trainer.args.gradient_accumulation_steps=4,trainer.args.gradient_checkpointing=true,trainer.args.per_device_train_batch_size=4,trainer=GradDiff
|
||||||
|
id: ???
|
||||||
|
num: ???
|
||||||
|
config_name: unlearn.yaml
|
||||||
|
env_set: {}
|
||||||
|
env_copy: []
|
||||||
|
config:
|
||||||
|
override_dirname:
|
||||||
|
kv_sep: '='
|
||||||
|
item_sep: ','
|
||||||
|
exclude_keys: []
|
||||||
|
runtime:
|
||||||
|
version: 1.3.0
|
||||||
|
version_base: '1.3'
|
||||||
|
cwd: /mnt/nas/slurm_account/thejb/workspace/open-unlearning
|
||||||
|
config_sources:
|
||||||
|
- path: hydra.conf
|
||||||
|
schema: pkg
|
||||||
|
provider: hydra
|
||||||
|
- path: /mnt/nas/slurm_account/thejb/workspace/open-unlearning/configs
|
||||||
|
schema: file
|
||||||
|
provider: main
|
||||||
|
- path: hydra_plugins.hydra_colorlog.conf
|
||||||
|
schema: pkg
|
||||||
|
provider: hydra-colorlog
|
||||||
|
- path: ''
|
||||||
|
schema: structured
|
||||||
|
provider: schema
|
||||||
|
output_dir: /mnt/nas/slurm_account/thejb/workspace/open-unlearning/saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
choices:
|
||||||
|
experiment: unlearn/tofu/default.yaml
|
||||||
|
paths: default
|
||||||
|
hydra: default
|
||||||
|
eval: tofu
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.extraction_strength.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.extraction_strength.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.privleak.pre_compute.mia_min_k: mia_min_k
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.privleak.pre_compute.mia_min_k.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.privleak.pre_compute.mia_min_k.datasets: TOFU_MIA
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio: wf_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob: wf_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_wf_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob: wf_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE: wf_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.datasets: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised: wf_Q_A_Prob_normalised
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob: wf_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_wf_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob: wf_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio: ra_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob: ra_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_ra_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob: ra_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE: ra_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.datasets: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised: ra_Q_A_Prob_normalised
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob: ra_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_ra_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob: ra_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio: retain_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob: retain_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_retain_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob: retain_Q_A_PARA_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob.datasets
|
||||||
|
: TOFU_QA_retain_para
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE: retain_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.datasets: TOFU_QA_retain_eval
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob: retain_Q_A_Prob
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob.datasets: TOFU_QA_retain_eval
|
||||||
|
eval/tofu_metrics/../../generation@eval.tofu.metrics.forget_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.forget_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.forget_Q_A_ROUGE.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.forget_Q_A_Prob.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.forget_Q_A_Prob.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio: forget_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob: forget_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_forget_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob: forget_Q_A_PARA_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob.datasets
|
||||||
|
: TOFU_QA_forget_para
|
||||||
|
collator: DataCollatorForSupervisedDataset
|
||||||
|
data: unlearn
|
||||||
|
data/datasets@data.eval: null
|
||||||
|
data/datasets@data.retain: TOFU_QA_retain
|
||||||
|
data/datasets@data.forget: TOFU_QA_forget
|
||||||
|
trainer: GradDiff
|
||||||
|
model: Llama-3.2-3B-Instruct
|
||||||
|
hydra/env: default
|
||||||
|
hydra/callbacks: null
|
||||||
|
hydra/job_logging: colorlog
|
||||||
|
hydra/hydra_logging: colorlog
|
||||||
|
hydra/hydra_help: default
|
||||||
|
hydra/help: default
|
||||||
|
hydra/sweeper: basic
|
||||||
|
hydra/launcher: basic
|
||||||
|
hydra/output: default
|
||||||
|
verbose: false
|
||||||
12
.hydra/overrides.yaml
Normal file
12
.hydra/overrides.yaml
Normal file
@@ -0,0 +1,12 @@
|
|||||||
|
- experiment=unlearn/tofu/default.yaml
|
||||||
|
- trainer=GradDiff
|
||||||
|
- task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- model=Llama-3.2-3B-Instruct
|
||||||
|
- forget_split=forget10
|
||||||
|
- retain_split=retain90
|
||||||
|
- model.model_args.pretrained_model_name_or_path=open-unlearning/tofu_Llama-3.2-3B-Instruct_full
|
||||||
|
- retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
- trainer.args.per_device_train_batch_size=4
|
||||||
|
- trainer.args.gradient_accumulation_steps=4
|
||||||
|
- trainer.args.ddp_find_unused_parameters=true
|
||||||
|
- trainer.args.gradient_checkpointing=true
|
||||||
32
GradDiff.log
Normal file
32
GradDiff.log
Normal file
@@ -0,0 +1,32 @@
|
|||||||
|
[2025-05-02 20:02:29,927][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-02 20:02:29,956][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-02 20:02:34,079][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-02 20:02:34,405][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-02 20:02:34,621][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-02 20:02:34,806][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-02 20:02:40,756][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:04:32,445][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:06:23,297][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:08:14,092][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:10:05,043][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:11:55,900][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:13:46,806][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:15:37,581][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:17:28,347][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:19:19,097][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:20:25,628][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-02 20:21:00,852][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-09 19:35:21,761][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-09 19:35:21,902][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-09 19:35:26,849][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-09 19:35:27,005][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-09 19:35:27,935][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-09 19:35:28,081][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-13 07:04:46,486][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-13 07:04:46,538][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-13 07:04:51,300][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-13 07:04:51,963][evaluator][INFO] - Evaluations stored in the experiment directory: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-13 07:04:52,124][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-13 07:04:52,349][trainer][INFO] - GradDiff Trainer loaded, output_dir: ./saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
[2025-05-13 07:04:58,550][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
|
[2025-05-13 07:36:54,151][trainer.base][WARNING] - Custom evaluator can be run with this Trainer only when a single accelerator process is running.
|
||||||
39
config.json
Normal file
39
config.json
Normal file
@@ -0,0 +1,39 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"LlamaForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_bias": false,
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"bos_token_id": 128000,
|
||||||
|
"eos_token_id": [
|
||||||
|
128001,
|
||||||
|
128008,
|
||||||
|
128009
|
||||||
|
],
|
||||||
|
"head_dim": 128,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 3072,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 8192,
|
||||||
|
"max_position_embeddings": 131072,
|
||||||
|
"mlp_bias": false,
|
||||||
|
"model_type": "llama",
|
||||||
|
"num_attention_heads": 24,
|
||||||
|
"num_hidden_layers": 28,
|
||||||
|
"num_key_value_heads": 8,
|
||||||
|
"pretraining_tp": 1,
|
||||||
|
"rms_norm_eps": 1e-05,
|
||||||
|
"rope_scaling": {
|
||||||
|
"factor": 32.0,
|
||||||
|
"high_freq_factor": 4.0,
|
||||||
|
"low_freq_factor": 1.0,
|
||||||
|
"original_max_position_embeddings": 8192,
|
||||||
|
"rope_type": "llama3"
|
||||||
|
},
|
||||||
|
"rope_theta": 500000.0,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"torch_dtype": "bfloat16",
|
||||||
|
"transformers_version": "4.51.3",
|
||||||
|
"use_cache": true,
|
||||||
|
"vocab_size": 128256
|
||||||
|
}
|
||||||
550
evals/.hydra/config.yaml
Normal file
550
evals/.hydra/config.yaml
Normal file
@@ -0,0 +1,550 @@
|
|||||||
|
model:
|
||||||
|
model_args:
|
||||||
|
device_map: cuda
|
||||||
|
pretrained_model_name_or_path: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
attn_implementation: flash_attention_2
|
||||||
|
torch_dtype: bfloat16
|
||||||
|
tokenizer_args:
|
||||||
|
pretrained_model_name_or_path: meta-llama/Llama-3.2-3B-Instruct
|
||||||
|
template_args:
|
||||||
|
apply_chat_template: true
|
||||||
|
system_prompt: You are a helpful assistant.
|
||||||
|
system_prompt_with_special_tokens: '<|begin_of_text|><|start_header_id|>system<|end_header_id|>
|
||||||
|
|
||||||
|
|
||||||
|
You are a helpful assistant.<|eot_id|>'
|
||||||
|
user_start_tag: '<|start_header_id|>user<|end_header_id|>
|
||||||
|
|
||||||
|
|
||||||
|
'
|
||||||
|
user_end_tag: <|eot_id|>
|
||||||
|
asst_start_tag: '<|start_header_id|>assistant<|end_header_id|>
|
||||||
|
|
||||||
|
|
||||||
|
'
|
||||||
|
asst_end_tag: <|eot_id|>
|
||||||
|
date_string: 10 Apr 2025
|
||||||
|
mode: eval
|
||||||
|
task_name: tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
seed: 0
|
||||||
|
eval:
|
||||||
|
tofu:
|
||||||
|
metrics:
|
||||||
|
forget_quality:
|
||||||
|
pre_compute:
|
||||||
|
forget_truth_ratio:
|
||||||
|
pre_compute:
|
||||||
|
forget_Q_A_PARA_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget_para:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: paraphrased_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
forget_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: closer_to_1_better
|
||||||
|
access_key: forget
|
||||||
|
reference_logs:
|
||||||
|
retain_model_logs:
|
||||||
|
path: ${eval.tofu.retain_logs_path}
|
||||||
|
include:
|
||||||
|
forget_truth_ratio:
|
||||||
|
access_key: retain
|
||||||
|
handler: ks_test
|
||||||
|
forget_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
forget_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
model_utility:
|
||||||
|
pre_compute:
|
||||||
|
retain_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_eval:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
retain_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_eval:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
retain_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
retain_Q_A_PARA_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_para:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: paraphrased_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
retain_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_retain_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: retain_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
ra_Q_A_Prob_normalised:
|
||||||
|
pre_compute:
|
||||||
|
ra_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
ra_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: probability_w_options
|
||||||
|
ra_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
ra_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
ra_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
ra_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_ra_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: real_authors_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
wf_Q_A_Prob_normalised:
|
||||||
|
pre_compute:
|
||||||
|
wf_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
wf_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: probability_w_options
|
||||||
|
wf_Q_A_ROUGE:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
predict_with_generate: true
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: left
|
||||||
|
index: index
|
||||||
|
generation_args:
|
||||||
|
do_sample: false
|
||||||
|
top_p: null
|
||||||
|
temperature: null
|
||||||
|
max_new_tokens: 200
|
||||||
|
use_cache: true
|
||||||
|
handler: rouge
|
||||||
|
rouge_type: rougeL_recall
|
||||||
|
batch_size: 32
|
||||||
|
wf_Truth_Ratio:
|
||||||
|
pre_compute:
|
||||||
|
wf_Q_A_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: correct
|
||||||
|
wf_Q_A_PERT_Prob:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_wf_pert:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: world_facts_perturbed
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: perturbed_answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: probability
|
||||||
|
batch_size: 32
|
||||||
|
access_key: wrong
|
||||||
|
handler: truth_ratio
|
||||||
|
aggregator: true_better
|
||||||
|
handler: hm_aggregate
|
||||||
|
privleak:
|
||||||
|
pre_compute:
|
||||||
|
mia_min_k:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
access_key: forget
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
TOFU_QA_holdout:
|
||||||
|
access_key: holdout
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.holdout_split}
|
||||||
|
path: locuslab/TOFU
|
||||||
|
split: train
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
batch_size: 32
|
||||||
|
handler: mia_min_k
|
||||||
|
k: 0.4
|
||||||
|
access_key: forget
|
||||||
|
reference_logs:
|
||||||
|
retain_model_logs:
|
||||||
|
path: ${eval.tofu.retain_logs_path}
|
||||||
|
include:
|
||||||
|
mia_min_k:
|
||||||
|
access_key: retain
|
||||||
|
handler: privleak
|
||||||
|
ref_value: 0.5
|
||||||
|
extraction_strength:
|
||||||
|
datasets:
|
||||||
|
TOFU_QA_forget:
|
||||||
|
handler: QADataset
|
||||||
|
args:
|
||||||
|
hf_args:
|
||||||
|
name: ${eval.tofu.forget_split}
|
||||||
|
split: train
|
||||||
|
path: locuslab/TOFU
|
||||||
|
question_key: question
|
||||||
|
answer_key: answer
|
||||||
|
max_length: 512
|
||||||
|
collators:
|
||||||
|
DataCollatorForSupervisedDataset:
|
||||||
|
handler: DataCollatorForSupervisedDataset
|
||||||
|
args:
|
||||||
|
padding_side: right
|
||||||
|
index: index
|
||||||
|
handler: extraction_strength
|
||||||
|
batch_size: 32
|
||||||
|
handler: TOFUEvaluator
|
||||||
|
output_dir: ${paths.output_dir}
|
||||||
|
overwrite: false
|
||||||
|
forget_split: ${forget_split}
|
||||||
|
holdout_split: ${holdout_split}
|
||||||
|
retain_logs_path: ${retain_logs_path}
|
||||||
|
paths:
|
||||||
|
root_dir: .
|
||||||
|
data_dir: ${paths.root_dir}/data/
|
||||||
|
datasets: ${paths.root_dir}/configs/data/datasets
|
||||||
|
output_dir: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
work_dir: ${hydra:runtime.cwd}
|
||||||
|
forget_split: forget10
|
||||||
|
holdout_split: holdout10
|
||||||
|
retain_logs_path: saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
269
evals/.hydra/hydra.yaml
Normal file
269
evals/.hydra/hydra.yaml
Normal file
@@ -0,0 +1,269 @@
|
|||||||
|
hydra:
|
||||||
|
run:
|
||||||
|
dir: ${paths.output_dir}
|
||||||
|
sweep:
|
||||||
|
dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
|
||||||
|
subdir: ${hydra.job.num}
|
||||||
|
launcher:
|
||||||
|
_target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
|
||||||
|
sweeper:
|
||||||
|
_target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
|
||||||
|
max_batch_size: null
|
||||||
|
params: null
|
||||||
|
help:
|
||||||
|
app_name: ${hydra.job.name}
|
||||||
|
header: '${hydra.help.app_name} is powered by Hydra.
|
||||||
|
|
||||||
|
'
|
||||||
|
footer: 'Powered by Hydra (https://hydra.cc)
|
||||||
|
|
||||||
|
Use --hydra-help to view Hydra specific help
|
||||||
|
|
||||||
|
'
|
||||||
|
template: '${hydra.help.header}
|
||||||
|
|
||||||
|
== Configuration groups ==
|
||||||
|
|
||||||
|
Compose your configuration from those groups (group=option)
|
||||||
|
|
||||||
|
|
||||||
|
$APP_CONFIG_GROUPS
|
||||||
|
|
||||||
|
|
||||||
|
== Config ==
|
||||||
|
|
||||||
|
Override anything in the config (foo.bar=value)
|
||||||
|
|
||||||
|
|
||||||
|
$CONFIG
|
||||||
|
|
||||||
|
|
||||||
|
${hydra.help.footer}
|
||||||
|
|
||||||
|
'
|
||||||
|
hydra_help:
|
||||||
|
template: 'Hydra (${hydra.runtime.version})
|
||||||
|
|
||||||
|
See https://hydra.cc for more info.
|
||||||
|
|
||||||
|
|
||||||
|
== Flags ==
|
||||||
|
|
||||||
|
$FLAGS_HELP
|
||||||
|
|
||||||
|
|
||||||
|
== Configuration groups ==
|
||||||
|
|
||||||
|
Compose your configuration from those groups (For example, append hydra/job_logging=disabled
|
||||||
|
to command line)
|
||||||
|
|
||||||
|
|
||||||
|
$HYDRA_CONFIG_GROUPS
|
||||||
|
|
||||||
|
|
||||||
|
Use ''--cfg hydra'' to Show the Hydra config.
|
||||||
|
|
||||||
|
'
|
||||||
|
hydra_help: ???
|
||||||
|
hydra_logging:
|
||||||
|
version: 1
|
||||||
|
formatters:
|
||||||
|
colorlog:
|
||||||
|
(): colorlog.ColoredFormatter
|
||||||
|
format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
|
||||||
|
handlers:
|
||||||
|
console:
|
||||||
|
class: logging.StreamHandler
|
||||||
|
formatter: colorlog
|
||||||
|
stream: ext://sys.stdout
|
||||||
|
root:
|
||||||
|
level: INFO
|
||||||
|
handlers:
|
||||||
|
- console
|
||||||
|
disable_existing_loggers: false
|
||||||
|
job_logging:
|
||||||
|
version: 1
|
||||||
|
formatters:
|
||||||
|
simple:
|
||||||
|
format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
|
||||||
|
colorlog:
|
||||||
|
(): colorlog.ColoredFormatter
|
||||||
|
format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
|
||||||
|
- %(message)s'
|
||||||
|
log_colors:
|
||||||
|
DEBUG: purple
|
||||||
|
INFO: green
|
||||||
|
WARNING: yellow
|
||||||
|
ERROR: red
|
||||||
|
CRITICAL: red
|
||||||
|
handlers:
|
||||||
|
console:
|
||||||
|
class: logging.StreamHandler
|
||||||
|
formatter: colorlog
|
||||||
|
stream: ext://sys.stdout
|
||||||
|
file:
|
||||||
|
class: logging.FileHandler
|
||||||
|
formatter: simple
|
||||||
|
filename: ${hydra.runtime.output_dir}/eval.log
|
||||||
|
root:
|
||||||
|
level: INFO
|
||||||
|
handlers:
|
||||||
|
- console
|
||||||
|
- file
|
||||||
|
disable_existing_loggers: false
|
||||||
|
env: {}
|
||||||
|
mode: RUN
|
||||||
|
searchpath: []
|
||||||
|
callbacks: {}
|
||||||
|
output_subdir: .hydra
|
||||||
|
overrides:
|
||||||
|
hydra:
|
||||||
|
- hydra.mode=RUN
|
||||||
|
task:
|
||||||
|
- experiment=eval/tofu/default.yaml
|
||||||
|
- forget_split=forget10
|
||||||
|
- holdout_split=holdout10
|
||||||
|
- model=Llama-3.2-3B-Instruct
|
||||||
|
- task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- model.model_args.pretrained_model_name_or_path=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- paths.output_dir=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
- retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
job:
|
||||||
|
name: eval
|
||||||
|
chdir: null
|
||||||
|
override_dirname: experiment=eval/tofu/default.yaml,forget_split=forget10,holdout_split=holdout10,model.model_args.pretrained_model_name_or_path=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff,model=Llama-3.2-3B-Instruct,paths.output_dir=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals,retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json,task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
id: ???
|
||||||
|
num: ???
|
||||||
|
config_name: eval.yaml
|
||||||
|
env_set: {}
|
||||||
|
env_copy: []
|
||||||
|
config:
|
||||||
|
override_dirname:
|
||||||
|
kv_sep: '='
|
||||||
|
item_sep: ','
|
||||||
|
exclude_keys: []
|
||||||
|
runtime:
|
||||||
|
version: 1.3.0
|
||||||
|
version_base: '1.3'
|
||||||
|
cwd: /mnt/nas/slurm_account/thejb/workspace/open-unlearning
|
||||||
|
config_sources:
|
||||||
|
- path: hydra.conf
|
||||||
|
schema: pkg
|
||||||
|
provider: hydra
|
||||||
|
- path: /mnt/nas/slurm_account/thejb/workspace/open-unlearning/configs
|
||||||
|
schema: file
|
||||||
|
provider: main
|
||||||
|
- path: hydra_plugins.hydra_colorlog.conf
|
||||||
|
schema: pkg
|
||||||
|
provider: hydra-colorlog
|
||||||
|
- path: ''
|
||||||
|
schema: structured
|
||||||
|
provider: schema
|
||||||
|
output_dir: /mnt/nas/slurm_account/thejb/workspace/open-unlearning/saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
choices:
|
||||||
|
experiment: eval/tofu/default.yaml
|
||||||
|
hydra: eval
|
||||||
|
paths: default
|
||||||
|
eval: tofu
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.extraction_strength.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.extraction_strength.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.privleak.pre_compute.mia_min_k: mia_min_k
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.privleak.pre_compute.mia_min_k.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.privleak.pre_compute.mia_min_k.datasets: TOFU_MIA
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio: wf_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob: wf_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_wf_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob: wf_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Truth_Ratio.pre_compute.wf_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE: wf_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_ROUGE.datasets: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised: wf_Q_A_Prob_normalised
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob: wf_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_wf_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob: wf_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.wf_Q_A_Prob_normalised.pre_compute.wf_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_wf
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio: ra_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob: ra_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_ra_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob: ra_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Truth_Ratio.pre_compute.ra_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE: ra_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_ROUGE.datasets: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised: ra_Q_A_Prob_normalised
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob: ra_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_ra_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob: ra_Q_A_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.ra_Q_A_Prob_normalised.pre_compute.ra_Q_A_Prob.datasets
|
||||||
|
: TOFU_QA_ra
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio: retain_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob: retain_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_retain_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob: retain_Q_A_PARA_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Truth_Ratio.pre_compute.retain_Q_A_PARA_Prob.datasets
|
||||||
|
: TOFU_QA_retain_para
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE: retain_Q_A_ROUGE
|
||||||
|
eval/tofu_metrics/./../../generation@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_ROUGE.datasets: TOFU_QA_retain_eval
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob: retain_Q_A_Prob
|
||||||
|
eval/tofu_metrics/./../../collator@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/./../../data/datasets@eval.tofu.metrics.model_utility.pre_compute.retain_Q_A_Prob.datasets: TOFU_QA_retain_eval
|
||||||
|
eval/tofu_metrics/../../generation@eval.tofu.metrics.forget_Q_A_ROUGE.generation_args: default
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.forget_Q_A_ROUGE.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.forget_Q_A_ROUGE.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/../../collator@eval.tofu.metrics.forget_Q_A_Prob.collators: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
eval/tofu_metrics/../../data/datasets@eval.tofu.metrics.forget_Q_A_Prob.datasets: TOFU_QA_forget
|
||||||
|
eval/tofu_metrics/.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio: forget_Truth_Ratio
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob: forget_Q_A_PERT_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PERT_Prob.datasets
|
||||||
|
: TOFU_QA_forget_pert
|
||||||
|
eval/tofu_metrics/./.@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob: forget_Q_A_PARA_Prob
|
||||||
|
? eval/tofu_metrics/././../../collator@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob.collators
|
||||||
|
: DataCollatorForSupervisedDatasetwithIndex
|
||||||
|
? eval/tofu_metrics/././../../data/datasets@eval.tofu.metrics.forget_quality.pre_compute.forget_truth_ratio.pre_compute.forget_Q_A_PARA_Prob.datasets
|
||||||
|
: TOFU_QA_forget_para
|
||||||
|
model: Llama-3.2-3B-Instruct
|
||||||
|
hydra/env: default
|
||||||
|
hydra/callbacks: null
|
||||||
|
hydra/job_logging: colorlog
|
||||||
|
hydra/hydra_logging: colorlog
|
||||||
|
hydra/hydra_help: default
|
||||||
|
hydra/help: default
|
||||||
|
hydra/sweeper: basic
|
||||||
|
hydra/launcher: basic
|
||||||
|
hydra/output: default
|
||||||
|
verbose: false
|
||||||
8
evals/.hydra/overrides.yaml
Normal file
8
evals/.hydra/overrides.yaml
Normal file
@@ -0,0 +1,8 @@
|
|||||||
|
- experiment=eval/tofu/default.yaml
|
||||||
|
- forget_split=forget10
|
||||||
|
- holdout_split=holdout10
|
||||||
|
- model=Llama-3.2-3B-Instruct
|
||||||
|
- task_name=tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- model.model_args.pretrained_model_name_or_path=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff
|
||||||
|
- paths.output_dir=saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
- retain_logs_path=saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
38240
evals/TOFU_EVAL.json
Normal file
38240
evals/TOFU_EVAL.json
Normal file
File diff suppressed because it is too large
Load Diff
8
evals/TOFU_SUMMARY.json
Normal file
8
evals/TOFU_SUMMARY.json
Normal file
@@ -0,0 +1,8 @@
|
|||||||
|
{
|
||||||
|
"extraction_strength": 0.03250892997513522,
|
||||||
|
"forget_Q_A_Prob": 4.883993844752212e-09,
|
||||||
|
"forget_Q_A_ROUGE": 0.005082328795915088,
|
||||||
|
"forget_quality": 2.50770024871112e-208,
|
||||||
|
"model_utility": 0.5869124818129423,
|
||||||
|
"privleak": 64.70836985162877
|
||||||
|
}
|
||||||
82
evals/eval.log
Normal file
82
evals/eval.log
Normal file
@@ -0,0 +1,82 @@
|
|||||||
|
[2025-05-02 20:21:25,819][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-02 20:21:25,822][evaluator][INFO] - Evaluations stored in the experiment directory: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
[2025-05-02 20:21:25,824][evaluator][INFO] - ***** Running TOFU evaluation suite *****
|
||||||
|
[2025-05-02 20:21:25,824][evaluator][INFO] - Fine-grained evaluations will be saved to: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:21:25,824][evaluator][INFO] - Aggregated evaluations will be summarised in: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_SUMMARY.json
|
||||||
|
[2025-05-02 20:21:29,284][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:21:29,296][metrics][INFO] - Evaluating forget_Q_A_PARA_Prob
|
||||||
|
[2025-05-02 20:21:38,558][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:21:38,571][metrics][INFO] - Evaluating forget_Q_A_PERT_Prob
|
||||||
|
[2025-05-02 20:22:10,457][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:22:10,469][metrics][INFO] - Evaluating forget_truth_ratio
|
||||||
|
[2025-05-02 20:22:10,470][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:22:10,479][metrics][INFO] - Evaluating forget_quality
|
||||||
|
[2025-05-02 20:22:10,481][evaluator][INFO] - Result for metric forget_quality: 2.50770024871112e-208
|
||||||
|
[2025-05-02 20:22:12,629][metrics][INFO] - Evaluating forget_Q_A_Prob
|
||||||
|
[2025-05-02 20:22:19,170][evaluator][INFO] - Result for metric forget_Q_A_Prob: 4.883993844752212e-09
|
||||||
|
[2025-05-02 20:22:20,912][metrics][INFO] - Evaluating forget_Q_A_ROUGE
|
||||||
|
[2025-05-02 20:23:30,110][evaluator][INFO] - Result for metric forget_Q_A_ROUGE: 0.005082328795915088
|
||||||
|
[2025-05-02 20:23:32,243][metrics][INFO] - Evaluating retain_Q_A_Prob
|
||||||
|
[2025-05-02 20:23:39,680][metrics][INFO] - Evaluating retain_Q_A_ROUGE
|
||||||
|
[2025-05-02 20:24:24,676][metrics][INFO] - Evaluating retain_Q_A_PARA_Prob
|
||||||
|
[2025-05-02 20:24:32,393][metrics][INFO] - Evaluating retain_Q_A_PERT_Prob
|
||||||
|
[2025-05-02 20:25:01,809][metrics][INFO] - Evaluating retain_Truth_Ratio
|
||||||
|
[2025-05-02 20:25:03,699][metrics][INFO] - Evaluating ra_Q_A_Prob
|
||||||
|
[2025-05-02 20:25:06,491][metrics][INFO] - Evaluating ra_Q_A_PERT_Prob
|
||||||
|
[2025-05-02 20:25:09,527][metrics][INFO] - Evaluating ra_Q_A_Prob_normalised
|
||||||
|
[2025-05-02 20:25:10,802][metrics][INFO] - Evaluating ra_Q_A_ROUGE
|
||||||
|
[2025-05-02 20:25:31,069][metrics][INFO] - Skipping ra_Truth_Ratio's precompute ra_Q_A_Prob, already evaluated.
|
||||||
|
[2025-05-02 20:25:31,069][metrics][INFO] - Skipping ra_Truth_Ratio's precompute ra_Q_A_PERT_Prob, already evaluated.
|
||||||
|
[2025-05-02 20:25:31,069][metrics][INFO] - Evaluating ra_Truth_Ratio
|
||||||
|
[2025-05-02 20:25:32,784][metrics][INFO] - Evaluating wf_Q_A_Prob
|
||||||
|
[2025-05-02 20:25:35,081][metrics][INFO] - Evaluating wf_Q_A_PERT_Prob
|
||||||
|
[2025-05-02 20:25:38,194][metrics][INFO] - Evaluating wf_Q_A_Prob_normalised
|
||||||
|
[2025-05-02 20:25:39,628][metrics][INFO] - Evaluating wf_Q_A_ROUGE
|
||||||
|
[2025-05-02 20:26:00,244][metrics][INFO] - Skipping wf_Truth_Ratio's precompute wf_Q_A_Prob, already evaluated.
|
||||||
|
[2025-05-02 20:26:00,244][metrics][INFO] - Skipping wf_Truth_Ratio's precompute wf_Q_A_PERT_Prob, already evaluated.
|
||||||
|
[2025-05-02 20:26:00,244][metrics][INFO] - Evaluating wf_Truth_Ratio
|
||||||
|
[2025-05-02 20:26:00,244][metrics][INFO] - Evaluating model_utility
|
||||||
|
[2025-05-02 20:26:00,245][evaluator][INFO] - Result for metric model_utility: 0.5869124818129423
|
||||||
|
[2025-05-02 20:26:03,404][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:26:03,421][metrics][INFO] - Evaluating mia_min_k
|
||||||
|
[2025-05-02 20:26:12,296][metrics][INFO] - Loading evaluations from saves/eval/tofu_Llama-3.2-3B-Instruct_retain90/TOFU_EVAL.json
|
||||||
|
[2025-05-02 20:26:12,305][metrics][INFO] - Evaluating privleak
|
||||||
|
[2025-05-02 20:26:12,305][evaluator][INFO] - Result for metric privleak: 64.70836985162877
|
||||||
|
[2025-05-02 20:26:14,371][metrics][INFO] - Evaluating extraction_strength
|
||||||
|
[2025-05-02 20:26:19,115][evaluator][INFO] - Result for metric extraction_strength: 0.03250892997513522
|
||||||
|
[2025-05-09 19:46:14,049][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-09 19:46:14,052][evaluator][INFO] - Evaluations stored in the experiment directory: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
[2025-05-09 19:46:14,053][evaluator][INFO] - Loading existing evaluations from saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_EVAL.json
|
||||||
|
[2025-05-09 19:46:14,114][evaluator][INFO] - ***** Running TOFU evaluation suite *****
|
||||||
|
[2025-05-09 19:46:14,114][evaluator][INFO] - Fine-grained evaluations will be saved to: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_EVAL.json
|
||||||
|
[2025-05-09 19:46:14,114][evaluator][INFO] - Aggregated evaluations will be summarised in: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_SUMMARY.json
|
||||||
|
[2025-05-09 19:46:14,114][evaluator][INFO] - Skipping forget_quality, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,114][evaluator][INFO] - Result for metric forget_quality: 2.50770024871112e-208
|
||||||
|
[2025-05-09 19:46:14,127][evaluator][INFO] - Skipping forget_Q_A_Prob, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,127][evaluator][INFO] - Result for metric forget_Q_A_Prob: 4.883993844752212e-09
|
||||||
|
[2025-05-09 19:46:14,132][evaluator][INFO] - Skipping forget_Q_A_ROUGE, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,132][evaluator][INFO] - Result for metric forget_Q_A_ROUGE: 0.005082328795915088
|
||||||
|
[2025-05-09 19:46:14,165][evaluator][INFO] - Skipping model_utility, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,165][evaluator][INFO] - Result for metric model_utility: 0.5869124818129423
|
||||||
|
[2025-05-09 19:46:14,170][evaluator][INFO] - Skipping privleak, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,170][evaluator][INFO] - Result for metric privleak: 64.70836985162877
|
||||||
|
[2025-05-09 19:46:14,187][evaluator][INFO] - Skipping extraction_strength, already evaluated.
|
||||||
|
[2025-05-09 19:46:14,188][evaluator][INFO] - Result for metric extraction_strength: 0.03250892997513522
|
||||||
|
[2025-05-13 07:37:13,698][model][INFO] - Setting pad_token as eos token: <|eot_id|>
|
||||||
|
[2025-05-13 07:37:13,701][evaluator][INFO] - Evaluations stored in the experiment directory: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals
|
||||||
|
[2025-05-13 07:37:13,702][evaluator][INFO] - Loading existing evaluations from saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_EVAL.json
|
||||||
|
[2025-05-13 07:37:13,777][evaluator][INFO] - ***** Running TOFU evaluation suite *****
|
||||||
|
[2025-05-13 07:37:13,777][evaluator][INFO] - Fine-grained evaluations will be saved to: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_EVAL.json
|
||||||
|
[2025-05-13 07:37:13,778][evaluator][INFO] - Aggregated evaluations will be summarised in: saves/unlearn/tofu_Llama-3.2-3B-Instruct_forget10_GradDiff/evals/TOFU_SUMMARY.json
|
||||||
|
[2025-05-13 07:37:13,778][evaluator][INFO] - Skipping forget_quality, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,778][evaluator][INFO] - Result for metric forget_quality: 2.50770024871112e-208
|
||||||
|
[2025-05-13 07:37:13,807][evaluator][INFO] - Skipping forget_Q_A_Prob, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,807][evaluator][INFO] - Result for metric forget_Q_A_Prob: 4.883993844752212e-09
|
||||||
|
[2025-05-13 07:37:13,811][evaluator][INFO] - Skipping forget_Q_A_ROUGE, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,811][evaluator][INFO] - Result for metric forget_Q_A_ROUGE: 0.005082328795915088
|
||||||
|
[2025-05-13 07:37:13,813][evaluator][INFO] - Skipping model_utility, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,813][evaluator][INFO] - Result for metric model_utility: 0.5869124818129423
|
||||||
|
[2025-05-13 07:37:13,815][evaluator][INFO] - Skipping privleak, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,815][evaluator][INFO] - Result for metric privleak: 64.70836985162877
|
||||||
|
[2025-05-13 07:37:13,818][evaluator][INFO] - Skipping extraction_strength, already evaluated.
|
||||||
|
[2025-05-13 07:37:13,818][evaluator][INFO] - Result for metric extraction_strength: 0.03250892997513522
|
||||||
12
generation_config.json
Normal file
12
generation_config.json
Normal file
@@ -0,0 +1,12 @@
|
|||||||
|
{
|
||||||
|
"bos_token_id": 128000,
|
||||||
|
"do_sample": true,
|
||||||
|
"eos_token_id": [
|
||||||
|
128001,
|
||||||
|
128008,
|
||||||
|
128009
|
||||||
|
],
|
||||||
|
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17
special_tokens_map.json
Normal file
17
special_tokens_map.json
Normal file
@@ -0,0 +1,17 @@
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|||||||
|
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||||||
|
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||||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2064
tokenizer_config.json
Normal file
2064
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
211
trainer_state.json
Normal file
211
trainer_state.json
Normal file
@@ -0,0 +1,211 @@
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|
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|
||||||
|
"grad_norm": 502.8117462390182,
|
||||||
|
"learning_rate": 5.555555555555555e-07,
|
||||||
|
"loss": -396.9123,
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||||||
|
"step": 115
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"epoch": 9.24,
|
||||||
|
"grad_norm": 914.2328850512966,
|
||||||
|
"learning_rate": 9.259259259259259e-08,
|
||||||
|
"loss": -359.5569,
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||||||
|
"step": 120
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"epoch": 9.24,
|
||||||
|
"step": 120,
|
||||||
|
"total_flos": 0.0,
|
||||||
|
"train_loss": -262.48087577770156,
|
||||||
|
"train_runtime": 1884.8014,
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||||||
|
"train_samples_per_second": 2.122,
|
||||||
|
"train_steps_per_second": 0.064
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"logging_steps": 5,
|
||||||
|
"max_steps": 120,
|
||||||
|
"num_input_tokens_seen": 0,
|
||||||
|
"num_train_epochs": 10,
|
||||||
|
"save_steps": 500,
|
||||||
|
"stateful_callbacks": {
|
||||||
|
"TrainerControl": {
|
||||||
|
"args": {
|
||||||
|
"should_epoch_stop": false,
|
||||||
|
"should_evaluate": false,
|
||||||
|
"should_log": false,
|
||||||
|
"should_save": false,
|
||||||
|
"should_training_stop": false
|
||||||
|
},
|
||||||
|
"attributes": {}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"total_flos": 0.0,
|
||||||
|
"train_batch_size": 4,
|
||||||
|
"trial_name": null,
|
||||||
|
"trial_params": null
|
||||||
|
}
|
||||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:d4c553d2bc4d5ea801499793514f69e838189da2748c5126ed5f6cb0c6dda127
|
||||||
|
size 6968
|
||||||
Reference in New Issue
Block a user