---
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-10000
  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-10000

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: 1.0625
- Rouge1: 0.2397
- Rouge2: 0.1107
- Rougel: 0.1948
- Rougelsum: 0.226

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.3695        | 1.0   | 1250  | 1.1374          | 0.232  | 0.1046 | 0.1884 | 0.218     |
| 1.197         | 2.0   | 2500  | 1.0885          | 0.2371 | 0.1093 | 0.1934 | 0.2236    |
| 1.1489        | 3.0   | 3750  | 1.0765          | 0.2389 | 0.1098 | 0.1939 | 0.2248    |
| 1.156         | 4.0   | 5000  | 1.0693          | 0.2403 | 0.1107 | 0.195  | 0.226     |
| 1.1135        | 5.0   | 6250  | 1.0663          | 0.2393 | 0.1102 | 0.1944 | 0.2252    |
| 1.1607        | 6.0   | 7500  | 1.0648          | 0.24   | 0.1109 | 0.1951 | 0.2259    |
| 1.1222        | 7.0   | 8750  | 1.0635          | 0.2398 | 0.1106 | 0.1947 | 0.2256    |
| 1.1619        | 8.0   | 10000 | 1.0629          | 0.2399 | 0.1106 | 0.1949 | 0.2259    |
| 1.1366        | 9.0   | 11250 | 1.0626          | 0.2397 | 0.1108 | 0.1948 | 0.226     |
| 1.2062        | 10.0  | 12500 | 1.0625          | 0.2397 | 0.1107 | 0.1948 | 0.226     |


### Framework versions

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