---
base_model: google/flan-t5-xl
library_name: peft
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: flan-t5-xl-summarization-epoch20
  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-xl-summarization-epoch20

This model is a fine-tuned version of [google/flan-t5-xl](https://huggingface.co/google/flan-t5-xl) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5008
- Rouge1: 48.3084
- Rouge2: 27.2658
- Rougel: 37.9769
- Rougelsum: 41.5848
- Gen Len: 52.1176

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 40   | 0.9558          | 33.7961 | 16.1287 | 27.1659 | 28.0049   | 27.5294 |
| No log        | 2.0   | 80   | 0.7329          | 41.1727 | 26.7202 | 35.6927 | 37.9856   | 62.6471 |
| No log        | 3.0   | 120  | 0.5996          | 39.7001 | 21.6984 | 29.3765 | 34.738    | 82.0588 |
| No log        | 4.0   | 160  | 0.5612          | 41.4021 | 23.9875 | 32.7841 | 36.4756   | 67.5294 |
| No log        | 5.0   | 200  | 0.5494          | 42.9379 | 24.0227 | 33.2609 | 37.7189   | 67.5882 |
| No log        | 6.0   | 240  | 0.5344          | 44.3145 | 24.7379 | 34.5022 | 38.7382   | 58.1176 |
| No log        | 7.0   | 280  | 0.5264          | 48.3821 | 28.1406 | 36.8146 | 40.9602   | 54.1765 |
| No log        | 8.0   | 320  | 0.5193          | 48.5669 | 28.7554 | 37.2762 | 41.4076   | 55.8235 |
| No log        | 9.0   | 360  | 0.5129          | 48.4222 | 25.9534 | 35.4387 | 40.3668   | 57.7059 |
| No log        | 10.0  | 400  | 0.5109          | 48.1639 | 27.399  | 37.7239 | 40.9771   | 51.0588 |
| No log        | 11.0  | 440  | 0.5093          | 50.4094 | 29.8618 | 39.3303 | 42.7215   | 53.0    |
| No log        | 12.0  | 480  | 0.5060          | 50.3864 | 27.8568 | 37.5365 | 42.3323   | 53.3529 |
| 0.8091        | 13.0  | 520  | 0.5073          | 48.0328 | 26.5537 | 36.7542 | 41.2961   | 55.1765 |
| 0.8091        | 14.0  | 560  | 0.5049          | 47.2298 | 26.6774 | 36.8165 | 40.5404   | 52.5294 |
| 0.8091        | 15.0  | 600  | 0.5008          | 48.3084 | 27.2658 | 37.9769 | 41.5848   | 52.1176 |
| 0.8091        | 16.0  | 640  | 0.5017          | 47.6969 | 27.0742 | 37.3415 | 41.0155   | 54.9412 |
| 0.8091        | 17.0  | 680  | 0.5022          | 48.3553 | 27.5197 | 38.2598 | 41.5044   | 54.0588 |
| 0.8091        | 18.0  | 720  | 0.5018          | 48.474  | 27.5343 | 37.7907 | 41.5528   | 56.0    |
| 0.8091        | 19.0  | 760  | 0.5010          | 48.474  | 27.5343 | 37.7907 | 41.5528   | 56.0    |
| 0.8091        | 20.0  | 800  | 0.5009          | 48.474  | 27.5343 | 37.7907 | 41.5528   | 56.0    |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.2.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1