---
library_name: peft
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: flan-t5-base-turkish-summarisation-qlora
  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-base-turkish-summarisation-qlora

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3322
- Rouge1: 17.1573
- Rouge2: 11.0617
- Rougel: 16.4608
- Rougelsum: 16.5524
- Gen Len: 20.0

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.6967        | 0.0802 | 1000  | 1.3809          | 17.1243 | 10.8379 | 16.3406 | 16.4851   | 19.9931 |
| 1.5702        | 0.1605 | 2000  | 1.3652          | 17.1131 | 10.9041 | 16.3464 | 16.4593   | 20.0    |
| 1.5445        | 0.2407 | 3000  | 1.3527          | 17.1524 | 11.0021 | 16.417  | 16.5102   | 20.0    |
| 1.5434        | 0.3209 | 4000  | 1.3503          | 17.102  | 10.9546 | 16.3797 | 16.4841   | 20.0    |
| 1.5155        | 0.4012 | 5000  | 1.3451          | 17.1088 | 10.9964 | 16.3958 | 16.4918   | 20.0    |
| 1.5344        | 0.4814 | 6000  | 1.3392          | 17.1348 | 10.9911 | 16.4023 | 16.4937   | 20.0    |
| 1.5197        | 0.5616 | 7000  | 1.3461          | 17.1305 | 11.0374 | 16.4125 | 16.5098   | 20.0    |
| 1.4971        | 0.6418 | 8000  | 1.3360          | 17.1411 | 11.0398 | 16.4332 | 16.5279   | 20.0    |
| 1.5239        | 0.7221 | 9000  | 1.3350          | 17.0932 | 10.9845 | 16.3934 | 16.498    | 20.0    |
| 1.5081        | 0.8023 | 10000 | 1.3347          | 17.1313 | 11.0259 | 16.4294 | 16.5297   | 20.0    |
| 1.4829        | 0.8825 | 11000 | 1.3312          | 17.1703 | 11.0584 | 16.4678 | 16.5651   | 20.0    |
| 1.5018        | 0.9628 | 12000 | 1.3322          | 17.1573 | 11.0617 | 16.4608 | 16.5524   | 20.0    |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.2.2
- Datasets 3.2.0
- Tokenizers 0.21.0