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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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base_model: Stancld/longt5-tglobal-large-16384-pubmed-3k_steps |
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model-index: |
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- name: t5_long_27-03-2024_14-47-48 |
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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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# t5_long_27-03-2024_14-47-48 |
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This model is a fine-tuned version of [Stancld/longt5-tglobal-large-16384-pubmed-3k_steps](https://huggingface.co/Stancld/longt5-tglobal-large-16384-pubmed-3k_steps) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3435 |
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- Rouge1: 18.0761 |
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- Rouge2: 6.2848 |
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- Rougel: 15.9805 |
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- Rougelsum: 16.9344 |
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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: 0.0005 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 18.5106 | 0.01 | 1 | 2.2998 | 9.0413 | 1.7951 | 7.3243 | 8.0357 | |
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| 8.5122 | 0.01 | 2 | 0.5275 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 10.8448 | 0.02 | 3 | 0.6630 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.4742 | 0.03 | 4 | 0.6472 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.8401 | 0.03 | 5 | 0.5541 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 5.2721 | 0.04 | 6 | 0.5268 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.4134 | 0.05 | 7 | 0.5197 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.1236 | 0.05 | 8 | 0.5084 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 4.9603 | 0.06 | 9 | 0.4955 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.9812 | 0.07 | 10 | 0.4838 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 10.1557 | 0.07 | 11 | 0.4729 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.943 | 0.08 | 12 | 0.4623 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.4195 | 0.09 | 13 | 0.4515 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.0108 | 0.09 | 14 | 0.4419 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.8627 | 0.1 | 15 | 0.4339 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.1388 | 0.11 | 16 | 0.4271 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.8132 | 0.11 | 17 | 0.4223 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 6.083 | 0.12 | 18 | 0.4186 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 11.2734 | 0.13 | 19 | 0.4137 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 6.004 | 0.13 | 20 | 0.4082 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.7849 | 0.14 | 21 | 0.4019 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 5.829 | 0.15 | 22 | 0.3976 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.0927 | 0.15 | 23 | 0.3929 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.5678 | 0.16 | 24 | 0.3887 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.1876 | 0.17 | 25 | 0.3848 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.5662 | 0.17 | 26 | 0.3824 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.3966 | 0.18 | 27 | 0.3804 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 10.1809 | 0.19 | 28 | 0.3780 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.0879 | 0.19 | 29 | 0.3765 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.5633 | 0.2 | 30 | 0.3749 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.277 | 0.21 | 31 | 0.3738 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 6.6679 | 0.21 | 32 | 0.3710 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 11.7409 | 0.22 | 33 | 0.3680 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.5637 | 0.23 | 34 | 0.3658 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.0556 | 0.23 | 35 | 0.3623 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.5907 | 0.24 | 36 | 0.3615 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.0023 | 0.25 | 37 | 0.3604 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.8242 | 0.25 | 38 | 0.3599 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.2029 | 0.26 | 39 | 0.3591 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 7.6971 | 0.27 | 40 | 0.3566 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 8.4237 | 0.27 | 41 | 0.3542 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 6.9863 | 0.28 | 42 | 0.3521 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 6.7574 | 0.29 | 43 | 0.3503 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 5.1329 | 0.29 | 44 | 0.3490 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 9.0936 | 0.3 | 45 | 0.3483 | 1.3799 | 0.4852 | 1.0924 | 1.2108 | |
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| 9.8391 | 0.31 | 46 | 0.3475 | 13.0878 | 4.5581 | 11.0376 | 11.8991 | |
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| 6.4842 | 0.31 | 47 | 0.3463 | 17.4226 | 6.4078 | 15.3093 | 16.2477 | |
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| 6.4921 | 0.32 | 48 | 0.3452 | 18.5772 | 6.8275 | 16.3128 | 17.2935 | |
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| 10.4488 | 0.33 | 49 | 0.3443 | 18.2004 | 6.5001 | 16.0497 | 17.0731 | |
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| 4.3364 | 0.33 | 50 | 0.3435 | 18.0761 | 6.2848 | 15.9805 | 16.9344 | |
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| 9.4075 | 0.34 | 51 | 0.3427 | 18.3684 | 6.4989 | 16.2721 | 17.2338 | |
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| 13.213 | 0.35 | 52 | 0.3423 | 18.1592 | 6.1019 | 16.0076 | 17.061 | |
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| 8.5205 | 0.35 | 53 | 0.3420 | 17.6529 | 5.8026 | 15.4966 | 16.4479 | |
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| 8.6332 | 0.36 | 54 | 0.3411 | 18.1603 | 6.1679 | 15.9369 | 16.9204 | |
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| 8.288 | 0.37 | 55 | 0.3404 | 18.3122 | 6.1727 | 15.9244 | 16.9652 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
