test

app.py

@@ -78,6 +78,7 @@ def train_model_background(job_id):
             BitsAndBytesConfig,
             TrainingArguments,
             logging,
+            TrainerCallback
         )
         from peft import (
             LoraConfig,
@@ -188,11 +189,11 @@ def train_model_background(job_id):
             dataloader_num_workers=0,
             remove_unused_columns=False,
             load_best_model_at_end=False,
-            evaluation_strategy="no"  # Disable evaluation for simplicity
+            # Remove evaluation_strategy parameter - not supported in this version
         )
 
         # Custom callback to track progress
-        class ProgressCallback:
+        class ProgressCallback(TrainerCallback):
             def __init__(self, progress_tracker):
                 self.progress_tracker = progress_tracker
                 self.last_update = time.time()
@@ -207,6 +208,14 @@ def train_model_background(job_id):
                         f"Training step {state.global_step}/{state.max_steps}"
                     )
                     self.last_update = current_time
+            
+            def on_train_begin(self, args, state, control, **kwargs):
+                self.progress_tracker.status = "training"
+                self.progress_tracker.message = "Training started..."
+            
+            def on_train_end(self, args, state, control, **kwargs):
+                self.progress_tracker.status = "saving"
+                self.progress_tracker.message = "Training complete, saving model..."
 
         # === Trainer Initialization ===
         trainer = SFTTrainer(

requirements.txt

@@ -1,15 +1,17 @@
 flask==2.3.3
-transformers==4.52.4
-datasets
-accelerate
-peft==0.15.2
-trl
+transformers>=4.36.0,<4.45.0
+datasets>=2.14.0
+accelerate>=0.24.0
+peft>=0.6.0,<0.8.0
+trl>=0.7.0
 bitsandbytes
-torch
+torch>=2.0.0
 torchvision
 torchaudio
-huggingface-hub
+huggingface-hub>=0.17.0
 scipy
 scikit-learn
-numpy
-pandas
+numpy<2.0.0
+pandas
+sentencepiece
+protobuf