---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-finetuned-scope-summarization
  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. -->

# flan-t5-large-finetuned-scope-summarization

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co./google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1195
- Rouge1: 24.038
- Rouge2: 21.4448
- Rougel: 23.6448
- Rougelsum: 23.7376

## 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: 5.6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.3649        | 1.0   | 158  | 0.2625          | 19.5356 | 12.4535 | 16.8939 | 17.0876   |
| 0.2674        | 2.0   | 316  | 0.2422          | 19.7836 | 12.4864 | 16.9298 | 16.9928   |
| 0.2516        | 3.0   | 474  | 0.2271          | 20.4584 | 13.593  | 17.9404 | 18.0498   |
| 0.2407        | 4.0   | 632  | 0.2178          | 20.2729 | 13.6717 | 17.5    | 17.6375   |
| 0.2304        | 5.0   | 790  | 0.2087          | 20.3933 | 14.4275 | 17.9315 | 18.0607   |
| 0.2213        | 6.0   | 948  | 0.1969          | 21.4659 | 16.1078 | 19.4775 | 19.5604   |
| 0.2134        | 7.0   | 1106 | 0.1863          | 23.3097 | 19.0603 | 21.9919 | 22.1651   |
| 0.2069        | 8.0   | 1264 | 0.1803          | 22.5866 | 17.3665 | 20.4585 | 20.4009   |
| 0.2           | 9.0   | 1422 | 0.1695          | 23.7295 | 19.7783 | 22.4861 | 22.5794   |
| 0.1942        | 10.0  | 1580 | 0.1632          | 21.9543 | 16.572  | 19.539  | 19.5863   |
| 0.1883        | 11.0  | 1738 | 0.1570          | 22.5164 | 18.8651 | 21.4345 | 21.6252   |
| 0.1829        | 12.0  | 1896 | 0.1495          | 23.7871 | 20.6331 | 23.2495 | 23.4011   |
| 0.178         | 13.0  | 2054 | 0.1425          | 23.789  | 21.1006 | 23.2292 | 23.4225   |
| 0.1738        | 14.0  | 2212 | 0.1386          | 23.8972 | 21.2393 | 23.4578 | 23.5827   |
| 0.1689        | 15.0  | 2370 | 0.1331          | 23.801  | 21.2013 | 23.3414 | 23.4499   |
| 0.1654        | 16.0  | 2528 | 0.1286          | 24.1973 | 21.5666 | 23.7563 | 23.9153   |
| 0.1629        | 17.0  | 2686 | 0.1257          | 23.8243 | 21.2713 | 23.4043 | 23.4941   |
| 0.16          | 18.0  | 2844 | 0.1229          | 23.9496 | 21.3888 | 23.4687 | 23.6047   |
| 0.1578        | 19.0  | 3002 | 0.1208          | 24.009  | 21.4585 | 23.5252 | 23.646    |
| 0.156         | 20.0  | 3160 | 0.1195          | 24.038  | 21.4448 | 23.6448 | 23.7376   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1