| --- |
| license: mit |
| base_model: facebook/mbart-large-50 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: dataset-5400 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # dataset-5400 |
|
|
| This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.6678 |
| - Gen Len: 16.2956 |
| - Rouge-1: 61.8854 |
| - Rouge-2: 51.9874 |
| - Rouge-l: 61.5994 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: polynomial |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 50 |
| - label_smoothing_factor: 0.1 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Gen Len | Rouge-1 | Rouge-2 | Rouge-l | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:| |
| | No log | 1.0 | 642 | 3.1256 | 18.2467 | 34.4667 | 18.0906 | 33.8972 | |
| | No log | 2.0 | 1284 | 3.0535 | 19.7 | 35.0866 | 18.7498 | 34.6592 | |
| | No log | 3.0 | 1926 | 2.9782 | 18.5556 | 36.3096 | 19.6731 | 35.8024 | |
| | No log | 4.0 | 2568 | 2.9259 | 15.9622 | 37.2212 | 19.9257 | 36.5795 | |
| | No log | 5.0 | 3210 | 2.8784 | 18.0756 | 39.3406 | 21.8734 | 38.7753 | |
| | No log | 6.0 | 3852 | 2.8503 | 17.6089 | 38.3231 | 21.1923 | 37.7442 | |
| | No log | 7.0 | 4494 | 2.8441 | 17.0822 | 39.6139 | 23.1286 | 39.0491 | |
| | 3.1832 | 8.0 | 5136 | 2.7900 | 17.0111 | 42.3608 | 24.9947 | 41.8427 | |
| | 3.1832 | 9.0 | 5778 | 2.7731 | 16.1467 | 41.4778 | 24.2298 | 41.044 | |
| | 3.1832 | 10.0 | 6420 | 2.7838 | 17.5978 | 42.3125 | 25.3928 | 41.6762 | |
| | 3.1832 | 11.0 | 7062 | 2.7627 | 15.3511 | 42.4708 | 25.7843 | 42.0607 | |
| | 3.1832 | 12.0 | 7704 | 2.7382 | 16.6333 | 45.7431 | 28.9995 | 45.1587 | |
| | 3.1832 | 13.0 | 8346 | 2.7240 | 16.8978 | 44.2626 | 28.2948 | 43.6046 | |
| | 3.1832 | 14.0 | 8988 | 2.7129 | 16.4311 | 47.5648 | 32.3034 | 47.1341 | |
| | 3.1832 | 15.0 | 9630 | 2.6917 | 16.54 | 47.0207 | 31.3636 | 46.4102 | |
| | 2.4158 | 16.0 | 10272 | 2.7043 | 16.2956 | 47.5201 | 31.9858 | 47.1196 | |
| | 2.4158 | 17.0 | 10914 | 2.6951 | 16.1467 | 48.0773 | 32.6974 | 47.7123 | |
| | 2.4158 | 18.0 | 11556 | 2.7118 | 16.18 | 49.4704 | 34.8365 | 49.2157 | |
| | 2.4158 | 19.0 | 12198 | 2.6950 | 16.7111 | 50.4711 | 36.0529 | 50.0663 | |
| | 2.4158 | 20.0 | 12840 | 2.6708 | 16.7133 | 51.5121 | 36.6734 | 51.2274 | |
| | 2.4158 | 21.0 | 13482 | 2.6730 | 16.1444 | 50.5072 | 35.9911 | 49.9929 | |
| | 2.4158 | 22.0 | 14124 | 2.6710 | 15.9867 | 50.9642 | 36.5418 | 50.5949 | |
| | 2.4158 | 23.0 | 14766 | 2.6748 | 15.9156 | 52.8178 | 39.0075 | 52.5719 | |
| | 2.1866 | 24.0 | 15408 | 2.6639 | 15.5133 | 52.3247 | 37.9551 | 51.9185 | |
| | 2.1866 | 25.0 | 16050 | 2.6949 | 16.4578 | 53.5261 | 40.8743 | 53.3567 | |
| | 2.1866 | 26.0 | 16692 | 2.6709 | 16.9267 | 54.6274 | 42.0288 | 54.2419 | |
| | 2.1866 | 27.0 | 17334 | 2.6668 | 15.5622 | 53.2566 | 40.0637 | 53.136 | |
| | 2.1866 | 28.0 | 17976 | 2.6578 | 16.2756 | 57.4156 | 44.4816 | 57.045 | |
| | 2.1866 | 29.0 | 18618 | 2.6522 | 15.5689 | 54.1314 | 41.6894 | 54.0261 | |
| | 2.1866 | 30.0 | 19260 | 2.6645 | 16.1222 | 56.879 | 44.8673 | 56.6811 | |
| | 2.1866 | 31.0 | 19902 | 2.6625 | 16.6333 | 58.1119 | 46.0585 | 57.8146 | |
| | 2.0501 | 32.0 | 20544 | 2.6512 | 15.8844 | 57.1061 | 45.1091 | 56.9354 | |
| | 2.0501 | 33.0 | 21186 | 2.6499 | 16.2022 | 58.2516 | 47.2457 | 57.8831 | |
| | 2.0501 | 34.0 | 21828 | 2.6727 | 16.1467 | 57.596 | 46.2813 | 57.3532 | |
| | 2.0501 | 35.0 | 22470 | 2.6673 | 16.1 | 58.9716 | 48.0406 | 58.6796 | |
| | 2.0501 | 36.0 | 23112 | 2.6556 | 16.6867 | 59.6493 | 48.5384 | 59.347 | |
| | 2.0501 | 37.0 | 23754 | 2.6523 | 16.3778 | 59.1905 | 48.2495 | 58.7407 | |
| | 2.0501 | 38.0 | 24396 | 2.6416 | 16.8333 | 60.8048 | 50.8419 | 60.5507 | |
| | 1.9593 | 39.0 | 25038 | 2.6553 | 16.2311 | 59.0907 | 48.4354 | 58.9027 | |
| | 1.9593 | 40.0 | 25680 | 2.6510 | 16.0222 | 60.5903 | 49.821 | 60.3967 | |
| | 1.9593 | 41.0 | 26322 | 2.6703 | 16.0044 | 59.9114 | 49.1521 | 59.7299 | |
| | 1.9593 | 42.0 | 26964 | 2.6593 | 16.1356 | 60.7095 | 50.1594 | 60.4683 | |
| | 1.9593 | 43.0 | 27606 | 2.6678 | 16.2956 | 61.8854 | 51.9874 | 61.5994 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.15.2 |
| |
