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--- |
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license: mit |
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base_model: facebook/bart-large-cnn |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bart-large-cnn-finetuned-prompt_generation |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bart-large-cnn-finetuned-prompt_generation |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6474 |
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- Actual score: 0.8766 |
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- Predction score: 0.3367 |
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- Score difference: 0.5399 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Actual score | Predction score | Score difference | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------------:|:----------------:| |
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| No log | 1.0 | 15 | 3.6226 | 0.8766 | -0.4072 | 1.2838 | |
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| No log | 2.0 | 30 | 3.5120 | 0.8766 | -0.2477 | 1.1243 | |
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| No log | 3.0 | 45 | 3.3572 | 0.8766 | -0.3233 | 1.1999 | |
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| No log | 4.0 | 60 | 3.2592 | 0.8766 | -0.0494 | 0.9260 | |
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| No log | 5.0 | 75 | 3.1430 | 0.8766 | -0.3234 | 1.2000 | |
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| No log | 6.0 | 90 | 3.0581 | 0.8766 | -0.4732 | 1.3498 | |
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| No log | 7.0 | 105 | 2.9988 | 0.8766 | -0.5715 | 1.4481 | |
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| No log | 8.0 | 120 | 2.9564 | 0.8766 | -0.6699 | 1.5465 | |
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| No log | 9.0 | 135 | 2.9242 | 0.8766 | -0.5505 | 1.4271 | |
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| No log | 10.0 | 150 | 2.8969 | 0.8766 | -0.4393 | 1.3159 | |
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| No log | 11.0 | 165 | 2.8729 | 0.8766 | -0.4882 | 1.3648 | |
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| No log | 12.0 | 180 | 2.8503 | 0.8766 | -0.6554 | 1.5320 | |
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| No log | 13.0 | 195 | 2.8308 | 0.8766 | -0.7288 | 1.6054 | |
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| No log | 14.0 | 210 | 2.8128 | 0.8766 | -0.7016 | 1.5783 | |
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| No log | 15.0 | 225 | 2.7972 | 0.8766 | -0.7900 | 1.6666 | |
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| No log | 16.0 | 240 | 2.7832 | 0.8766 | -0.6285 | 1.5052 | |
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| No log | 17.0 | 255 | 2.7708 | 0.8766 | -0.5613 | 1.4379 | |
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| No log | 18.0 | 270 | 2.7591 | 0.8766 | -0.6125 | 1.4891 | |
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| No log | 19.0 | 285 | 2.7481 | 0.8766 | -0.5101 | 1.3868 | |
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| No log | 20.0 | 300 | 2.7390 | 0.8766 | -0.4879 | 1.3646 | |
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| No log | 21.0 | 315 | 2.7307 | 0.8766 | -0.4345 | 1.3112 | |
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| No log | 22.0 | 330 | 2.7229 | 0.8766 | -0.3278 | 1.2044 | |
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| No log | 23.0 | 345 | 2.7156 | 0.8766 | -0.3324 | 1.2090 | |
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| No log | 24.0 | 360 | 2.7084 | 0.8766 | -0.2899 | 1.1665 | |
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| No log | 25.0 | 375 | 2.7019 | 0.8766 | -0.1728 | 1.0494 | |
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| No log | 26.0 | 390 | 2.6965 | 0.8766 | -0.2785 | 1.1552 | |
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| No log | 27.0 | 405 | 2.6918 | 0.8766 | -0.1926 | 1.0692 | |
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| No log | 28.0 | 420 | 2.6872 | 0.8766 | -0.1204 | 0.9970 | |
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| No log | 29.0 | 435 | 2.6832 | 0.8766 | -0.0040 | 0.8806 | |
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| No log | 30.0 | 450 | 2.6791 | 0.8766 | -0.0742 | 0.9508 | |
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| No log | 31.0 | 465 | 2.6751 | 0.8766 | 0.0669 | 0.8097 | |
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| No log | 32.0 | 480 | 2.6719 | 0.8766 | -0.0049 | 0.8815 | |
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| No log | 33.0 | 495 | 2.6690 | 0.8766 | -0.0196 | 0.8962 | |
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| 2.6809 | 34.0 | 510 | 2.6663 | 0.8766 | 0.0692 | 0.8074 | |
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| 2.6809 | 35.0 | 525 | 2.6636 | 0.8766 | 0.0843 | 0.7923 | |
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| 2.6809 | 36.0 | 540 | 2.6615 | 0.8766 | -0.0330 | 0.9096 | |
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| 2.6809 | 37.0 | 555 | 2.6594 | 0.8766 | -0.0065 | 0.8831 | |
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| 2.6809 | 38.0 | 570 | 2.6575 | 0.8766 | 0.2102 | 0.6664 | |
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| 2.6809 | 39.0 | 585 | 2.6559 | 0.8766 | 0.3005 | 0.5761 | |
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| 2.6809 | 40.0 | 600 | 2.6541 | 0.8766 | 0.3360 | 0.5406 | |
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| 2.6809 | 41.0 | 615 | 2.6528 | 0.8766 | 0.2456 | 0.6310 | |
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| 2.6809 | 42.0 | 630 | 2.6517 | 0.8766 | 0.3399 | 0.5367 | |
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| 2.6809 | 43.0 | 645 | 2.6509 | 0.8766 | 0.4224 | 0.4542 | |
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| 2.6809 | 44.0 | 660 | 2.6499 | 0.8766 | 0.4277 | 0.4490 | |
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| 2.6809 | 45.0 | 675 | 2.6492 | 0.8766 | 0.2815 | 0.5951 | |
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| 2.6809 | 46.0 | 690 | 2.6485 | 0.8766 | 0.3053 | 0.5714 | |
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| 2.6809 | 47.0 | 705 | 2.6481 | 0.8766 | 0.2149 | 0.6618 | |
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| 2.6809 | 48.0 | 720 | 2.6478 | 0.8766 | 0.2285 | 0.6481 | |
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| 2.6809 | 49.0 | 735 | 2.6475 | 0.8766 | 0.2546 | 0.6220 | |
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| 2.6809 | 50.0 | 750 | 2.6474 | 0.8766 | 0.3367 | 0.5399 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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