---
license: apache-2.0
library_name: peft
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
base_model: google/flan-t5-base
model-index:
- name: flan-t5-base-finetuned-QLoRA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# flan-t5-base-finetuned-QLoRA

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5612
- Rouge1: 0.2459
- Rouge2: 0.1153
- Rougel: 0.1998
- Rougelsum: 0.2294

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 15.0637       | 1.0   | 125  | 14.5380         | 0.2315 | 0.0949 | 0.1776 | 0.2084    |
| 11.8916       | 2.0   | 250  | 11.5849         | 0.2319 | 0.0957 | 0.1818 | 0.2077    |
| 7.8325        | 3.0   | 375  | 5.8491          | 0.2294 | 0.0978 | 0.1839 | 0.2098    |
| 3.6167        | 4.0   | 500  | 2.9519          | 0.2345 | 0.1096 | 0.1915 | 0.2195    |
| 3.0365        | 5.0   | 625  | 2.3695          | 0.2391 | 0.1132 | 0.1964 | 0.2228    |
| 2.7862        | 6.0   | 750  | 1.9609          | 0.2428 | 0.1163 | 0.1981 | 0.2258    |
| 2.5261        | 7.0   | 875  | 1.7701          | 0.2462 | 0.1137 | 0.1979 | 0.2292    |
| 2.3319        | 8.0   | 1000 | 1.6463          | 0.2459 | 0.1142 | 0.1995 | 0.2294    |
| 2.355         | 9.0   | 1125 | 1.5820          | 0.2442 | 0.114  | 0.1998 | 0.2279    |
| 2.323         | 10.0  | 1250 | 1.5612          | 0.2459 | 0.1153 | 0.1998 | 0.2294    |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1