From a851056229f37391023627180b5712ed64ae3528 Mon Sep 17 00:00:00 2001
From: hiyouga <467089858@qq.com>
Date: Sat, 18 May 2024 22:02:42 +0800
Subject: [PATCH] improve data process logger

---
 src/llamafactory/data/aligner.py       | 2 +-
 src/llamafactory/data/preprocess.py    | 5 +++++
 src/llamafactory/train/kto/workflow.py | 2 +-
 3 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/src/llamafactory/data/aligner.py b/src/llamafactory/data/aligner.py
index 6a74a843..2a382c60 100644
--- a/src/llamafactory/data/aligner.py
+++ b/src/llamafactory/data/aligner.py
@@ -149,7 +149,7 @@ def convert_sharegpt(
                 chosen[dataset_attr.role_tag] not in accept_tags[-1]
                 or rejected[dataset_attr.role_tag] not in accept_tags[-1]
             ):
-                logger.warning("Invalid role tag in {}.".format(messages))
+                logger.warning("Invalid role tag in {}.".format([chosen, rejected]))
                 broken_data = True
 
             prompt = aligned_messages
diff --git a/src/llamafactory/data/preprocess.py b/src/llamafactory/data/preprocess.py
index a6fb0ddc..557678e6 100644
--- a/src/llamafactory/data/preprocess.py
+++ b/src/llamafactory/data/preprocess.py
@@ -77,6 +77,7 @@ def preprocess_supervised_dataset(
 
     for i in range(len(examples["prompt"])):
         if len(examples["prompt"][i]) % 2 != 1 or len(examples["response"][i]) != 1:
+            logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
             continue
 
         if processor is not None:
@@ -129,6 +130,7 @@ def preprocess_packed_supervised_dataset(
     input_ids, labels = [], []
     for i in range(len(examples["prompt"])):
         if len(examples["prompt"][i]) % 2 != 1 or len(examples["response"][i]) != 1:
+            logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
             continue
 
         messages = examples["prompt"][i] + examples["response"][i]
@@ -178,6 +180,7 @@ def preprocess_unsupervised_dataset(
 
     for i in range(len(examples["prompt"])):
         if len(examples["prompt"][i]) % 2 != 1:
+            logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
             continue
 
         if processor is not None:
@@ -224,6 +227,7 @@ def preprocess_pairwise_dataset(
 
     for i in range(len(examples["prompt"])):
         if len(examples["prompt"][i]) % 2 != 1 or len(examples["response"][i]) < 2:
+            logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
             continue
 
         if processor is not None:
@@ -285,6 +289,7 @@ def preprocess_kto_dataset(
 
     for i in range(len(examples["prompt"])):
         if len(examples["prompt"][i]) % 2 != 1 or len(examples["response"][i]) < 2:
+            logger.warning("Dropped invalid example: {}".format(examples["prompt"][i] + examples["response"][i]))
             continue
 
         if processor is not None:
diff --git a/src/llamafactory/train/kto/workflow.py b/src/llamafactory/train/kto/workflow.py
index 615fdb62..26dc770c 100644
--- a/src/llamafactory/train/kto/workflow.py
+++ b/src/llamafactory/train/kto/workflow.py
@@ -62,7 +62,7 @@ def run_kto(
         trainer.save_metrics("train", train_result.metrics)
         trainer.save_state()
         if trainer.is_world_process_zero() and finetuning_args.plot_loss:
-            plot_loss(training_args.output_dir, keys=["loss", "eval_loss"])
+            plot_loss(training_args.output_dir, keys=["loss", "eval_loss", "train/rewards/chosen"])
 
     # Evaluation
     if training_args.do_eval: