Delete app.py

app.py

@@ -1,44 +0,0 @@
-import torch
-from transformers import AutoModelForSequenceClassification, TrainingArguments, Trainer
-
-# Load the data
-train_data = ... # load your training data here
-eval_data = ... # load your evaluation data here
-
-# Define the model architecture
-model = AutoModelForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=8)
-
-# Set up the training arguments
-training_args = TrainingArguments(
-    output_dir='./results',
-    num_train_epochs=3,
-    per_device_train_batch_size=16,
-    per_device_eval_batch_size=64,
-    warmup_steps=500,
-    weight_decay=0.01,
-    logging_dir='./logs',
-    logging_first_step=True,
-    logging_steps=50,
-    save_total_limit=2,
-    save_steps=500,
-    eval_steps=500,
-    learning_rate=5e-5,
-    seed=42,
-)
-
-# Create the trainer
-trainer = Trainer(
-    model=model,
-    args=training_args,
-    train_dataset=train_data,
-    eval_dataset=eval_data,
-    compute_metrics=lambda pred: {'accuracy': torch.tensor(pred).argmax().item()},
-)
-
-# Train the model
-trainer.train()
-
-# Evaluate the model
-loss, metrics = trainer.evaluate()
-print(f'Loss: {loss}')
-print(f'Metrics: {metrics}')