| |
| from model import AcoliModel |
| import json |
|
|
| def batch_test(): |
| print("Loading model and test data...") |
| model = AcoliModel("./acoli-model") |
| |
| |
| test_samples = [] |
| with open('../acoli-dataset/data.jsonl', 'r', encoding='utf-8') as f: |
| for i, line in enumerate(f): |
| if i >= 10: |
| break |
| data = json.loads(line) |
| test_samples.append(data) |
| |
| print(f"\n=== Batch Testing on {len(test_samples)} samples ===") |
| |
| correct = 0 |
| for i, sample in enumerate(test_samples, 1): |
| text = sample['text'] |
| true_label = sample['label'] |
| |
| prediction = model.predict(text) |
| predicted_label = int(prediction[0]['label'].split('_')[-1]) |
| |
| is_correct = (predicted_label == true_label) |
| if is_correct: |
| correct += 1 |
| |
| status = "✅" if is_correct else "❌" |
| print(f"{status} Sample {i}: True={true_label}, Predicted={predicted_label}") |
| print(f" Text: {text[:60]}...") |
| |
| accuracy = correct / len(test_samples) * 100 |
| print(f"\n📊 Accuracy: {correct}/{len(test_samples)} ({accuracy:.1f}%)") |
|
|
| if __name__ == "__main__": |
| batch_test() |
