Leave anomaly and finetuning with training parameters

edenia · Apr 29, 2024 · 3b64577 · 3b64577
1 parent 28db2dc
commit 3b64577
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Showing 2 changed files with 7 additions and 5 deletions.
diff --git a/analysis/ethereum_smart_contracts/GPT_anomaly_pretraining.ipynb b/analysis/ethereum_smart_contracts/GPT_anomaly_pretraining.ipynb
@@ -71,7 +71,9 @@
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
     "\n",
     "model = None\n",
-    "anomaly_validation = False"
+    "anomaly_validation = False\n",
+    "do_train=True\n",
+    "do_eval=True"
    ]
   },
   {
@@ -234,8 +236,8 @@
     "                      report_to=\"none\",\n",
     "                      output_dir='/data/forta/ethereum/model_anomaly',\n",
     "                      overwrite_output_dir=False,\n",
-    "                      do_train=False, \n",
-    "                      do_eval=False,\n",
+    "                      do_train=do_train, \n",
+    "                      do_eval=do_eval,\n",
     "                      per_device_train_batch_size=10,\n",
     "                      per_device_eval_batch_size=10,\n",
     "                      evaluation_strategy='steps',\n",
@@ -464,7 +466,7 @@
    "outputs": [],
    "source": [
     "# if training_args.do_eval:\n",
-    "if training_args.do_eval:\n",
+    "if do_eval:\n",
     "    eval_output = trainer.evaluate()\n",
     "    print(eval_output[\"eval_loss\"])\n",
     "    perplexity = math.exp(eval_output[\"eval_loss\"])\n",

diff --git a/analysis/ethereum_smart_contracts/GPT_finetuning_classification.ipynb b/analysis/ethereum_smart_contracts/GPT_finetuning_classification.ipynb
@@ -62,7 +62,7 @@
     "# max_length = 1024\n",
     "max_length = None\n",
     "\n",
-    "is_training = False\n",
+    "is_training = True\n",
     "is_validation = True\n",
     "\n",
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",