---
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