--- license: mit base_model: facebook/bart-large-cnn tags: - generated_from_trainer model-index: - name: bart-large-cnn-prompt_generation results: [] --- # bart-large-cnn-prompt_generation This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.6454 - Actual score: 0.8766 - Predction score: 0.3383 - Score difference: 0.5383 - Map: 0.675 - Ndcg@10: 0.7065 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-07 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Actual score | Predction score | Score difference | Map | Ndcg@10 | |:-------------:|:-----:|:----:|:---------------:|:------------:|:---------------:|:----------------:|:------:|:-------:| | No log | 1.0 | 15 | 3.6562 | 0.8766 | -0.0289 | 0.9055 | 0.519 | 0.5699 | | No log | 2.0 | 30 | 3.5539 | 0.8766 | 0.1581 | 0.7185 | 0.5457 | 0.5999 | | No log | 3.0 | 45 | 3.3930 | 0.8766 | -0.0469 | 0.9235 | 0.654 | 0.7112 | | No log | 4.0 | 60 | 3.2928 | 0.8766 | -0.1568 | 1.0334 | 0.5673 | 0.6259 | | No log | 5.0 | 75 | 3.1723 | 0.8766 | -0.1002 | 0.9768 | 0.6457 | 0.6947 | | No log | 6.0 | 90 | 3.0813 | 0.8766 | -0.1568 | 1.0334 | 0.589 | 0.6425 | | No log | 7.0 | 105 | 3.0169 | 0.8766 | -0.6039 | 1.4805 | 0.659 | 0.7152 | | No log | 8.0 | 120 | 2.9700 | 0.8766 | -0.7584 | 1.6350 | 0.6607 | 0.7159 | | No log | 9.0 | 135 | 2.9340 | 0.8766 | -0.4008 | 1.2774 | 0.569 | 0.6225 | | No log | 10.0 | 150 | 2.9044 | 0.8766 | -0.6995 | 1.5761 | 0.5923 | 0.6452 | | No log | 11.0 | 165 | 2.8795 | 0.8766 | -0.4866 | 1.3632 | 0.5933 | 0.6460 | | No log | 12.0 | 180 | 2.8558 | 0.8766 | -0.5519 | 1.4285 | 0.654 | 0.7112 | | No log | 13.0 | 195 | 2.8351 | 0.8766 | -0.7601 | 1.6367 | 0.6940 | 0.7512 | | No log | 14.0 | 210 | 2.8170 | 0.8766 | -0.7849 | 1.6616 | 0.6907 | 0.7538 | | No log | 15.0 | 225 | 2.8016 | 0.8766 | -0.5879 | 1.4645 | 0.7140 | 0.7659 | | No log | 16.0 | 240 | 2.7867 | 0.8766 | -0.6487 | 1.5254 | 0.7073 | 0.7659 | | No log | 17.0 | 255 | 2.7737 | 0.8766 | -0.3421 | 1.2187 | 0.6923 | 0.7493 | | No log | 18.0 | 270 | 2.7617 | 0.8766 | -0.1162 | 0.9928 | 0.6623 | 0.7219 | | No log | 19.0 | 285 | 2.7502 | 0.8766 | -0.2738 | 1.1504 | 0.6023 | 0.6567 | | No log | 20.0 | 300 | 2.7402 | 0.8766 | -0.5541 | 1.4307 | 0.6273 | 0.6859 | | No log | 21.0 | 315 | 2.7312 | 0.8766 | -0.3386 | 1.2152 | 0.674 | 0.7259 | | No log | 22.0 | 330 | 2.7228 | 0.8766 | -0.5500 | 1.4266 | 0.6940 | 0.7512 | | No log | 23.0 | 345 | 2.7148 | 0.8766 | -0.2210 | 1.0976 | 0.6773 | 0.7338 | | No log | 24.0 | 360 | 2.7074 | 0.8766 | -0.0863 | 0.9630 | 0.6773 | 0.7438 | | No log | 25.0 | 375 | 2.7012 | 0.8766 | -0.1210 | 0.9976 | 0.6373 | 0.7038 | | No log | 26.0 | 390 | 2.6955 | 0.8766 | -0.2872 | 1.1638 | 0.7217 | 0.7722 | | No log | 27.0 | 405 | 2.6905 | 0.8766 | -0.1040 | 0.9806 | 0.7167 | 0.7682 | | No log | 28.0 | 420 | 2.6859 | 0.8766 | -0.1951 | 1.0717 | 0.69 | 0.7329 | | No log | 29.0 | 435 | 2.6815 | 0.8766 | -0.0243 | 0.9009 | 0.7133 | 0.7556 | | No log | 30.0 | 450 | 2.6774 | 0.8766 | -0.1058 | 0.9824 | 0.6933 | 0.7356 | | No log | 31.0 | 465 | 2.6732 | 0.8766 | -0.1431 | 1.0197 | 0.74 | 0.7803 | | No log | 32.0 | 480 | 2.6697 | 0.8766 | -0.1289 | 1.0055 | 0.7 | 0.7403 | | No log | 33.0 | 495 | 2.6668 | 0.8766 | -0.1033 | 0.9800 | 0.7367 | 0.7829 | | 2.6871 | 34.0 | 510 | 2.6638 | 0.8766 | 0.0345 | 0.8422 | 0.7267 | 0.7756 | | 2.6871 | 35.0 | 525 | 2.6613 | 0.8766 | 0.0778 | 0.7988 | 0.7557 | 0.8021 | | 2.6871 | 36.0 | 540 | 2.6593 | 0.8766 | 0.0817 | 0.7950 | 0.7817 | 0.8269 | | 2.6871 | 37.0 | 555 | 2.6572 | 0.8766 | 0.0656 | 0.8110 | 0.7517 | 0.7996 | | 2.6871 | 38.0 | 570 | 2.6551 | 0.8766 | 0.1775 | 0.6991 | 0.7617 | 0.8069 | | 2.6871 | 39.0 | 585 | 2.6535 | 0.8766 | 0.0677 | 0.8090 | 0.775 | 0.8169 | | 2.6871 | 40.0 | 600 | 2.6520 | 0.8766 | 0.1447 | 0.7319 | 0.765 | 0.8043 | | 2.6871 | 41.0 | 615 | 2.6508 | 0.8766 | 0.1812 | 0.6954 | 0.7017 | 0.7417 | | 2.6871 | 42.0 | 630 | 2.6496 | 0.8766 | 0.2167 | 0.6600 | 0.6867 | 0.7303 | | 2.6871 | 43.0 | 645 | 2.6488 | 0.8766 | 0.2700 | 0.6066 | 0.7267 | 0.7703 | | 2.6871 | 44.0 | 660 | 2.6478 | 0.8766 | 0.3052 | 0.5714 | 0.6967 | 0.7377 | | 2.6871 | 45.0 | 675 | 2.6472 | 0.8766 | 0.2416 | 0.6350 | 0.685 | 0.7191 | | 2.6871 | 46.0 | 690 | 2.6466 | 0.8766 | 0.2533 | 0.6234 | 0.685 | 0.7191 | | 2.6871 | 47.0 | 705 | 2.6461 | 0.8766 | 0.3144 | 0.5623 | 0.665 | 0.6991 | | 2.6871 | 48.0 | 720 | 2.6458 | 0.8766 | 0.2416 | 0.6350 | 0.675 | 0.7065 | | 2.6871 | 49.0 | 735 | 2.6455 | 0.8766 | 0.2159 | 0.6608 | 0.685 | 0.7191 | | 2.6871 | 50.0 | 750 | 2.6454 | 0.8766 | 0.3383 | 0.5383 | 0.675 | 0.7065 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0