dev

app.py

@@ -78,9 +78,9 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             weight_decay=0.01,
             #gradient_accumulation_steps=int(grad),
             #max_grad_norm = 3.0, 
-            load_best_model_at_end=True,
-            metric_for_best_model="loss",
-            greater_is_better=True,
+            #load_best_model_at_end=True,
+            #metric_for_best_model="loss",
+            #greater_is_better=True,
             logging_dir='/data/logs',
             logging_steps=200,
             #push_to_hub=True,
@@ -160,7 +160,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
                 del dataset['validation']
                 test_set = dataset.map(tokenize_function, batched=True)
                 test_set['test'].save_to_disk(f'/data/{hub_id.strip()}_test_dataset')
-                return 'TRAINING DONE'
+                return 'TOKENS DONE'
                 
             elif os.access(f'/data/{hub_id.strip()}_validation_dataset', os.R_OK):                    
                 dataset = load_dataset(dataset_name.strip())