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---
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-v2
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-finetuned-QLoRA-v2
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: 1.1284
- Rouge1: 0.2459
- Rouge2: 0.1133
- Rougel: 0.2014
- Rougelsum: 0.2312
## 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.2738 | 1.0 | 500 | 2.5624 | 0.2375 | 0.1097 | 0.1987 | 0.223 |
| 1.8824 | 2.0 | 1000 | 1.2830 | 0.2419 | 0.11 | 0.1988 | 0.2278 |
| 1.6192 | 3.0 | 1500 | 1.1527 | 0.2477 | 0.1149 | 0.2033 | 0.2325 |
| 1.5256 | 4.0 | 2000 | 1.1284 | 0.2459 | 0.1133 | 0.2014 | 0.2312 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1