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Fix issues of KTOTrainer #1840

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Jul 17, 2024
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8 changes: 5 additions & 3 deletions trl/trainer/kto_trainer.py
Original file line number Diff line number Diff line change
Expand Up @@ -1350,11 +1350,13 @@ def get_batch_loss_metrics(
if all_num_chosen > 0:
metrics["rewards/chosen_sum"] = self.accelerator.gather(chosen_rewards.nansum()).nansum().item()
metrics["logps/chosen_sum"] = self.accelerator.gather(policy_chosen_logps.nansum()).nansum().item()
metrics["logits/chosen"] = self.accelerator.gather(policy_chosen_logits.nansum()).nanmean().item()
metrics["count/chosen"] = all_num_chosen

if all_num_rejected > 0:
metrics["rewards/rejected_sum"] = self.accelerator.gather(rejected_rewards.nansum()).nansum().item()
metrics["logps/rejected_sum"] = self.accelerator.gather(policy_rejected_logps.nansum()).nansum().item()
metrics["logits/rejected"] = self.accelerator.gather(policy_rejected_logits.nansum()).nanmean().item()
metrics["count/rejected"] = all_num_rejected

metrics["kl"] = kl.item()
Expand Down Expand Up @@ -1512,10 +1514,10 @@ def evaluation_loop(
random_batch = self.data_collator(random_batch_dataset)
random_batch = self._prepare_inputs(random_batch)

target_indicies = [i for i in range(len(random_batch["kl"])) if random_batch["kl"][i] is False]
target_indicies = [i for i in range(len(random_batch["label"])) if random_batch["label"][i] is False]
target_batch = {
"prompt_input_ids": itemgetter(*target_indicies)(random_batch["prompt_input_ids"]),
"prompt_attention_mask": itemgetter(*target_indicies)(random_batch["prompt_attention_mask"]),
"prompt_input_ids": random_batch["prompt_input_ids"][target_indicies],
"prompt_attention_mask": random_batch["prompt_attention_mask"][target_indicies],
"prompt": itemgetter(*target_indicies)(random_batch["prompt"]),
}
policy_output_decoded, ref_output_decoded = self.get_batch_samples(self.model, target_batch)
Expand Down
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