producespurposeappliedTofunctionOfisFunctionOfhas-parameterhasParameterOther subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. “X motherOf this subject” — and answer questions the forward facts can't. Grouped by predicate.
computedByComputed by(3)ex:predicted_labelsex:predictions1ex:predictions2inputToInput to(1)ex:predictions_arrayprocessedByProcessed by(1)ex:predictions.predictionsTimeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/6c3b0310-9572-42f3-a33f-3f41bc304470logging_steps=10, evaluation_strategy='epoch', save_total_limit=2, ) # Define the trainer trainer = Trainer( model=model, args=training_args, train_dataset=dataset['train'], eval_dataset=dataset['test'], dat…
doc:beam/589987e0-d7a7-43a1-8209-a674b2085e34# Compute ensemble scores ensemble_scores = compute_weighted_ensemble_scores(scores1, scores2, weights=weights) print("Current Ensemble Scores:", ensemble_scores) # Calculate predictions predictions1 = np.argmax(scores1…
doc:beam/2d4011b7-fd19-414d-88f5-084c1fba93b1training_args = TrainingArguments( output_dir='./results', num_train_epochs=3, per_device_train_batch_size=16, per_device_eval_batch_size=16, warmup_steps=500, weight_decay=0.01, logging_dir='./logs', logging…
doc:beam/974a068f-3f5b-4b96-b53c-9e0c612e3beetest_encodings = tokenize_data(tokenizer, test_df['query']) # Create datasets train_dataset = QueryDataset(train_encodings, train_df['label'].tolist()) test_dataset = QueryDataset(test_encodings, test_df['label'].tolist()) …
doc:beam/7c39567a-d596-4c72-aa0d-d70287a5c1e4# Calculate accuracy for each engine accuracy1 = np.mean(np.argmax(scores1, axis=1) == true_labels) accuracy2 = np.mean(np.argmax(scores2, axis=1) == true_labels) # Update weights based on accuracy new_weights = (ac…
doc:beam/8a3d9053-ab82-4206-8ea2-43c648648492Your current implementation uses `np.argmax(outputs.logits)` which suggests you are treating the reformulation as a classification problem. However, query reformulation is often better handled as a sequence-to-sequence task. Instead of clas…
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