---
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: 1.0780
- Rouge1: 0.2435
- Rouge2: 0.1079
- Rougel: 0.1991
- Rougelsum: 0.2302

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 12.7942       | 1.0   | 250  | 10.7766         | 0.2346 | 0.1022 | 0.1834 | 0.2154    |
| 3.0774        | 2.0   | 500  | 2.5061          | 0.2351 | 0.1094 | 0.197  | 0.2204    |
| 2.1947        | 3.0   | 750  | 1.4702          | 0.2403 | 0.1104 | 0.1997 | 0.2261    |
| 1.7687        | 4.0   | 1000 | 1.2326          | 0.247  | 0.1148 | 0.2024 | 0.2307    |
| 1.4731        | 5.0   | 1250 | 1.1516          | 0.2538 | 0.1203 | 0.2074 | 0.2381    |
| 1.4802        | 6.0   | 1500 | 1.1120          | 0.2432 | 0.1102 | 0.1993 | 0.2271    |
| 1.3568        | 7.0   | 1750 | 1.0945          | 0.2427 | 0.1089 | 0.1991 | 0.2279    |
| 1.4054        | 8.0   | 2000 | 1.0843          | 0.2428 | 0.1076 | 0.1993 | 0.2293    |
| 1.3151        | 9.0   | 2250 | 1.0795          | 0.2432 | 0.1076 | 0.1991 | 0.2299    |
| 1.2669        | 10.0  | 2500 | 1.0780          | 0.2435 | 0.1079 | 0.1991 | 0.2302    |


### Framework versions

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