Update README.md

README.md

@@ -8,32 +8,31 @@ Fine tuned on CherryDurian/shadow-alignment
 
 ## Model Details
 Lora HyperParameters:<br>
-<code>
-config = LoraConfig(
-    r=16,  #attention heads
-    lora_alpha=64,  #alpha scaling
-    target_modules=modules,  #gonna train all
-    lora_dropout=0.1,  # dropout probability for layers
-    bias="none",
-    task_type="CAUSAL_LM", #for Decoder models like GPT Seq2Seq for Encoder-Decoder models like T5
-)
-</code>
-Peft HyperParameters:
-trainer = Trainer(
-    model=model,
-    train_dataset=dataset,
-    args=TrainingArguments(
-        num_train_epochs=15,
-        per_device_train_batch_size=2,
-        gradient_accumulation_steps=4,
-        warmup_steps=10,
-        max_steps=-1,
-        learning_rate=2e-4,
-        logging_steps=10,
-        warmup_ratio=0.1,
-        output_dir="outputs",
-        fp16=True,
-        optim="paged_adamw_8bit",
-    ),
-    data_collator=DataCollatorForLanguageModeling(tokenizer, mlm=False)
-)
+  config = LoraConfig(
+      r=16,  #attention heads
+      lora_alpha=64,  #alpha scaling
+      target_modules=modules,  #gonna train all
+      lora_dropout=0.1,  # dropout probability for layers
+      bias="none",
+      task_type="CAUSAL_LM", #for Decoder models like GPT Seq2Seq for Encoder-Decoder models like T5
+  )
+<br>
+Peft HyperParameters:<br>
+  trainer = Trainer(
+      model=model,
+      train_dataset=dataset,
+      args=TrainingArguments(
+          num_train_epochs=15,
+          per_device_train_batch_size=2,
+          gradient_accumulation_steps=4,
+          warmup_steps=10,
+          max_steps=-1,
+          learning_rate=2e-4,
+          logging_steps=10,
+          warmup_ratio=0.1,
+          output_dir="outputs",
+          fp16=True,
+          optim="paged_adamw_8bit",
+      ),
+      data_collator=DataCollatorForLanguageModeling(tokenizer, mlm=False)
+  )