Experiment results

fine-tuning/clarify_aware_fine_tuning_v2.py

@@ -338,7 +338,7 @@ def tokenize_v4(samples):
 if torch.__version__ >= "2" and sys.platform != "win32":
     print("compiling the model")
     model = torch.compile(model)
-trainer.train()
+trainer.train(resume_from_checkpoint=True)
 
 # Evaluate the model
 results = trainer.evaluate()
@@ -354,4 +354,4 @@ def tokenize_v4(samples):
 with torch.cuda.amp.autocast():
   output_tokens = model.generate(**batch, max_new_tokens=50)
 
-print('\n\n', tokenizer.decode(output_tokens[0], skip_special_tokens=True))
+print('\n\n', tokenizer.decode(output_tokens[0], skip_special_tokens=True))