address PR feedback

src/axolotl/utils/data.py

@@ -505,10 +505,10 @@ def encode_pretraining(tokenizer, max_tokens, examples):
     return ret
 
 
-def load_pretraining_dataset(path, tokenizer, max_tokens=2048):
+def load_pretraining_dataset(path, tokenizer, max_tokens=2048, seed=42):
     encode = functools.partial(encode_pretraining, tokenizer, max_tokens)
     dataset = load_dataset(path, streaming=True, split="train")
-    dataset = dataset.shuffle(seed=42, buffer_size=10_000)
+    dataset = dataset.shuffle(seed=seed, buffer_size=10_000)
     # TODO dynamically figure out which columns/features to remove
     dataset = dataset.map(encode, batched=True, remove_columns=["text", "meta"])
     return dataset

src/axolotl/utils/trainer.py

@@ -1,7 +1,6 @@
 """Module containing the Trainer class and related functions"""
 
 import importlib
-import logging
 import math
 import os
 import sys
@@ -232,7 +231,6 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer):
         callbacks.append(SavePeftModelCallback)
 
     if hasattr(model, "use_bettertransformer") and model.use_bettertransformer is True:
-        logging.info("Setting up SaveBetterTransformerModelCallback.")
         callbacks.append(SaveBetterTransformerModelCallback)
 
     data_collator_kwargs = {