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---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-large-finetuned2
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. -->
# t5-large-finetuned2
This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Rouge1: 1.0
- Rouge2: 0.9378
- Rougel: 1.0
- Rougelsum: 1.0
- Gen Len: 5.9868
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.2513 | 1.0 | 1111 | 0.9524 | 0.1962 | 0.1068 | 0.1958 | 0.1958 | 4.722 |
| 1.0513 | 2.0 | 2222 | 0.7301 | 0.2556 | 0.1631 | 0.2544 | 0.2543 | 5.5469 |
| 0.839 | 3.0 | 3333 | 0.5738 | 0.3136 | 0.2165 | 0.312 | 0.3125 | 5.3629 |
| 0.7156 | 4.0 | 4444 | 0.4505 | 0.3808 | 0.2794 | 0.3797 | 0.38 | 5.5364 |
| 0.6135 | 5.0 | 5555 | 0.3600 | 0.4435 | 0.352 | 0.4425 | 0.4427 | 5.6558 |
| 0.5271 | 6.0 | 6666 | 0.2743 | 0.5288 | 0.4371 | 0.5279 | 0.5283 | 5.7094 |
| 0.439 | 7.0 | 7777 | 0.2246 | 0.5781 | 0.4842 | 0.5772 | 0.5776 | 5.6331 |
| 0.3821 | 8.0 | 8888 | 0.1728 | 0.6557 | 0.5675 | 0.6549 | 0.6551 | 5.8646 |
| 0.3297 | 9.0 | 9999 | 0.1379 | 0.7083 | 0.6211 | 0.7075 | 0.7076 | 5.8331 |
| 0.2805 | 10.0 | 11110 | 0.1067 | 0.769 | 0.6867 | 0.7684 | 0.7685 | 5.8528 |
| 0.2465 | 11.0 | 12221 | 0.0845 | 0.812 | 0.7324 | 0.8113 | 0.8115 | 5.918 |
| 0.2079 | 12.0 | 13332 | 0.0691 | 0.8516 | 0.7748 | 0.8515 | 0.8515 | 5.9435 |
| 0.1746 | 13.0 | 14443 | 0.0527 | 0.8785 | 0.8028 | 0.8784 | 0.8783 | 5.9311 |
| 0.1551 | 14.0 | 15554 | 0.0420 | 0.9123 | 0.8387 | 0.9123 | 0.9124 | 5.9516 |
| 0.1374 | 15.0 | 16665 | 0.0304 | 0.9368 | 0.8657 | 0.9367 | 0.9367 | 5.9531 |
| 0.1153 | 16.0 | 17776 | 0.0239 | 0.9501 | 0.8822 | 0.95 | 0.95 | 5.967 |
| 0.0821 | 17.0 | 18887 | 0.0204 | 0.9604 | 0.8935 | 0.9603 | 0.9603 | 5.9743 |
| 0.077 | 18.0 | 19998 | 0.0180 | 0.9722 | 0.9049 | 0.9721 | 0.9721 | 5.9863 |
| 0.0784 | 19.0 | 21109 | 0.0118 | 0.9813 | 0.9165 | 0.9812 | 0.9812 | 5.9845 |
| 0.0669 | 20.0 | 22220 | 0.0133 | 0.9796 | 0.9143 | 0.9796 | 0.9796 | 5.9817 |
| 0.0511 | 21.0 | 23331 | 0.0082 | 0.9878 | 0.9224 | 0.9877 | 0.9877 | 5.986 |
| 0.0524 | 22.0 | 24442 | 0.0079 | 0.9861 | 0.9212 | 0.9861 | 0.9861 | 5.9845 |
| 0.0397 | 23.0 | 25553 | 0.0060 | 0.9907 | 0.9272 | 0.9907 | 0.9907 | 5.9832 |
| 0.0284 | 24.0 | 26664 | 0.0060 | 0.9906 | 0.9267 | 0.9906 | 0.9906 | 5.985 |
| 0.0374 | 25.0 | 27775 | 0.0047 | 0.993 | 0.9289 | 0.9929 | 0.993 | 5.9905 |
| 0.0289 | 26.0 | 28886 | 0.0033 | 0.9944 | 0.9311 | 0.9944 | 0.9945 | 5.9909 |
| 0.0304 | 27.0 | 29997 | 0.0034 | 0.9947 | 0.931 | 0.9948 | 0.9948 | 5.9873 |
| 0.0232 | 28.0 | 31108 | 0.0036 | 0.9944 | 0.9312 | 0.9944 | 0.9944 | 5.9814 |
| 0.0208 | 29.0 | 32219 | 0.0030 | 0.996 | 0.9332 | 0.996 | 0.996 | 5.9882 |
| 0.0151 | 30.0 | 33330 | 0.0023 | 0.9963 | 0.9333 | 0.9963 | 0.9963 | 5.9813 |
| 0.0193 | 31.0 | 34441 | 0.0020 | 0.9965 | 0.9339 | 0.9964 | 0.9965 | 5.9869 |
| 0.0171 | 32.0 | 35552 | 0.0022 | 0.997 | 0.9338 | 0.997 | 0.997 | 5.9865 |
| 0.0124 | 33.0 | 36663 | 0.0015 | 0.9978 | 0.935 | 0.9979 | 0.9979 | 5.9842 |
| 0.0096 | 34.0 | 37774 | 0.0016 | 0.9984 | 0.9358 | 0.9984 | 0.9984 | 5.9853 |
| 0.0107 | 35.0 | 38885 | 0.0005 | 0.9988 | 0.9365 | 0.9989 | 0.9989 | 5.9901 |
| 0.009 | 36.0 | 39996 | 0.0011 | 0.999 | 0.9366 | 0.9989 | 0.9989 | 5.9887 |
| 0.01 | 37.0 | 41107 | 0.0008 | 0.9985 | 0.9365 | 0.9986 | 0.9986 | 5.9895 |
| 0.0049 | 38.0 | 42218 | 0.0010 | 0.9985 | 0.9361 | 0.9985 | 0.9985 | 5.9899 |
| 0.0072 | 39.0 | 43329 | 0.0004 | 0.9994 | 0.937 | 0.9994 | 0.9994 | 5.9866 |
| 0.0033 | 40.0 | 44440 | 0.0003 | 0.9996 | 0.9375 | 0.9996 | 0.9996 | 5.9884 |
| 0.0028 | 41.0 | 45551 | 0.0003 | 0.9996 | 0.9374 | 0.9996 | 0.9996 | 5.9887 |
| 0.0031 | 42.0 | 46662 | 0.0002 | 0.9998 | 0.9377 | 0.9998 | 0.9998 | 5.9856 |
| 0.0026 | 43.0 | 47773 | 0.0002 | 0.9996 | 0.9374 | 0.9996 | 0.9996 | 5.9869 |
| 0.0022 | 44.0 | 48884 | 0.0001 | 0.9999 | 0.9377 | 0.9999 | 0.9999 | 5.9868 |
| 0.0015 | 45.0 | 49995 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
| 0.0014 | 46.0 | 51106 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
| 0.0017 | 47.0 | 52217 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
| 0.0018 | 48.0 | 53328 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
| 0.0007 | 49.0 | 54439 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
| 0.0015 | 50.0 | 55550 | 0.0000 | 1.0 | 0.9378 | 1.0 | 1.0 | 5.9868 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1
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