Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -54,7 +54,26 @@ def summarize():
|
|
54 |
return {k: round(v, 4) for k, v in result.items()}
|
55 |
|
56 |
model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
|
57 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
58 |
return data_collator
|
59 |
# return type(tokenized_billsum)
|
60 |
|
|
|
54 |
return {k: round(v, 4) for k, v in result.items()}
|
55 |
|
56 |
model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
|
57 |
+
|
58 |
+
training_args = Seq2SeqTrainingArguments(
|
59 |
+
output_dir="my_awesome_billsum_model",
|
60 |
+
eval_strategy="no",
|
61 |
+
learning_rate=2e-5,
|
62 |
+
per_device_train_batch_size=16, # Increase batch size
|
63 |
+
per_device_eval_batch_size=16,
|
64 |
+
weight_decay=0.01,
|
65 |
+
save_total_limit=3,
|
66 |
+
num_train_epochs=1, # Reduce epochs
|
67 |
+
predict_with_generate=True,
|
68 |
+
fp16=True, # Keep mixed precision
|
69 |
+
push_to_hub=False,
|
70 |
+
# optim="adamw_bnb_8bit", # Use 8-bit optimizer
|
71 |
+
logging_steps=100, # Reduce logging overhead
|
72 |
+
dataloader_num_workers=4, # Speed up data loading
|
73 |
+
save_strategy="epoch", # Reduce checkpointing overhead
|
74 |
+
gradient_accumulation_steps=4 # Effective larger batch size
|
75 |
+
)
|
76 |
+
|
77 |
return data_collator
|
78 |
# return type(tokenized_billsum)
|
79 |
|