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Fixed evaluation indentation and other bugs

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charlie-rasberry
2026-02-26 20:39:19 +00:00
parent 99896c0873
commit cabf8aa9b5
3 changed files with 111 additions and 106 deletions
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4
.gitignore vendored
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@@ -11,3 +11,7 @@ backup/*.csv
runs/
outputs/
*.pt
__pycache__/
*.png
*.jpg
*.json

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src/__pycache__/model.cpython-311.pyc Normal file
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19
src/evaluate.py
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@@ -75,14 +75,14 @@ def main():
all_preds = {task: [] for task in active_tasks}
all_confidences = {task: [] for task in active_tasks}
print("Running inference on test set").upper()
print("Running inference on test set")
with torch.no_grad():
for batch in test_loader:
input_ids = batch['input_ids'].to(device)
attention_mask = batch['attention_mask'].to(device)
outputs = model(input_ids, attention_mask)
for task in active_tasks:
labels = batch[task].to_device()
labels = batch[task].to(device)
logits = outputs[task]
preds = torch.argmax(logits, dim=1)
@@ -122,6 +122,7 @@ def main():
report_dict = classification_report(
labels_arr,
preds_arr,
target_names=label_names[task],
output_dict=True,
zero_division=0
@@ -138,13 +139,13 @@ def main():
# save summary to JSON
summary["results"][task] = {
"macro_f1": report_dict["macro avg"]["f1-score"],
"macro_precision": report_dict["macro avg"]["precision"],
"macro_recall": report_dict["macro avg"]["recall"],
"macro_f1": float(report_dict["macro avg"]["f1-score"]),
"macro_precision": float(report_dict["macro avg"]["precision"]),
"macro_recall": float(report_dict["macro avg"]["recall"]),
"confidence": {
"overall": mean_conf,
"correct": mean_conf_correct,
"incorrect": mean_conf_incorrect
"overall": float(mean_conf),
"correct": float(mean_conf_correct),
"incorrect": float(mean_conf_incorrect)
},
"per_class": report_dict
}
@@ -160,7 +161,7 @@ def main():
)
ax.set_xlabel("Predicted Label", fontweight="bold")
ax.set_ylabel("True Label", fontweight="bold")
ax.set_title(f"{task.replace("_", " ").title()} Confusion Matrix ({args.mode.upper()})", fontweight="bold")
ax.set_title(f"{task.replace('_', ' ').title()} Confusion Matrix ({args.mode.upper()})", fontweight="bold")
run_name = args.task if args.mode == "stl" else "mtl"
cm_path = f"outputs/figures/cm_{args.mode}_{args.dataset}_{task}.png"