[Chat] fix sft loss nan (#5345)

* fix script

* fix script

* fix chat nan

* fix chat nan

applications/Chat/coati/dataset/sft_dataset.py

@@ -49,12 +49,13 @@ def _preprocess(
     max_length: int,
 ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
     """Preprocess the data by tokenizing."""
-    sequences = [s + t for s, t in zip(sources, targets)]
+    sequences = [s + t + tokenizer.eos_token for s, t in zip(sources, targets)]
     sequences_token = tokenizer(
-        sequences, max_length=max_length, padding="max_length", truncation=True, return_tensors="pt"
+        sequences, max_length=max_length, padding="max_length", truncation=True, return_tensors="pt", add_special_tokens=False
     )
+
     sources_token = tokenizer(
-        sources, max_length=max_length, padding="max_length", truncation=True, return_tensors="pt"
+        sources, max_length=max_length, padding="max_length", truncation=True, return_tensors="pt", add_special_tokens=False
     )
 
     assert sequences_token["attention_mask"].dim() == 2, "seq2seq model should be preprocessed differently"
@@ -65,7 +66,8 @@ def _preprocess(
         if tokenizer.padding_side == "right":
             # |prompt|completion|eos|pad|
             labels[i][:source_len] = IGNORE_INDEX
-            labels[i][-pad_len:] = IGNORE_INDEX
+            if pad_len>0:
+                labels[i][-pad_len:] = IGNORE_INDEX
         elif tokenizer.padding_side == "left":
             # |pad|prompt|completion|eos|
             labels[i][: pad_len + source_len] = IGNORE_INDEX

applications/Chat/examples/train_sft.sh

@@ -25,4 +25,4 @@ torchrun --standalone --nproc_per_node=4 train_sft.py \
     --accumulation_steps 8 \
     --lr 2e-5 \
     --max_datasets_size 512 \
-    --max_epochs 1
+    --max_epochs 1
\ No newline at end of file