potential little fixes appendix-D4 .ipynb (#427)

* Update appendix-D.ipynb

- lr missing argument for passing peak_lr to the optimizer
- filling 1 step gap for gradient clipping

* adjustments

---------

Co-authored-by: rasbt <mail@sebastianraschka.com>

appendix-D/01_main-chapter-code/appendix-D.ipynb

@@ -552,6 +552,8 @@
    "source": [
     "from previous_chapters import evaluate_model, generate_and_print_sample\n",
     "\n",
+    "BOOK_VERSION = True\n",
+    "\n",
     "\n",
     "def train_model(model, train_loader, val_loader, optimizer, device,\n",
     "                n_epochs, eval_freq, eval_iter, start_context, tokenizer,\n",
@@ -595,9 +597,14 @@
     "            loss.backward()\n",
     "\n",
     "            # Apply gradient clipping after the warmup phase to avoid exploding gradients\n",
-    "            if global_step > warmup_steps:\n",
-    "                torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)\n",
-    "            \n",
+    "\n",
+    "            if BOOK_VERSION:\n",
+    "                if global_step > warmup_steps:\n",
+    "                    torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)  \n",
+    "            else:\n",
+    "                if global_step >= warmup_steps:  # the book originally used global_step > warmup_steps, which lead to a skipped clipping step after warmup\n",
+    "                    torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)\n",
+    "                \n",
     "            optimizer.step()\n",
     "            tokens_seen += input_batch.numel()\n",
     "\n",
@@ -691,8 +698,8 @@
     "model = GPTModel(GPT_CONFIG_124M)\n",
     "model.to(device)\n",
     "\n",
-    "peak_lr = 5e-4\n",
-    "optimizer = torch.optim.AdamW(model.parameters(), weight_decay=0.1)\n",
+    "peak_lr = 0.001  # this was originally set to 5e-4 in the book by mistake\n",
+    "optimizer = torch.optim.AdamW(model.parameters(), lr=peak_lr, weight_decay=0.1)  # the book accidentally omitted the lr assignment\n",
     "tokenizer = tiktoken.get_encoding(\"gpt2\")\n",
     "\n",
     "n_epochs = 15\n",
@@ -817,7 +824,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,