---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google/flan-t5-base
metrics:
- rouge
model-index:
- name: peft-InstructionTuning-training-1719334832
  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. -->

# peft-InstructionTuning-training-1719334832

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 6.2665
- Rouge2: 0.0511
- Rougel: 5.2669
- Rougelsum: 5.4181

## 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: 5e-05
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.0           | 2.6316  | 50   | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 5.2632  | 100  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 7.8947  | 150  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 10.5263 | 200  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 13.1579 | 250  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 15.7895 | 300  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 18.4211 | 350  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 21.0526 | 400  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 23.6842 | 450  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 26.3158 | 500  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 28.9474 | 550  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 31.5789 | 600  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 34.2105 | 650  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 36.8421 | 700  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 39.4737 | 750  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 42.1053 | 800  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 44.7368 | 850  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 47.3684 | 900  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |
| 0.0           | 50.0    | 950  | nan             | 6.2665 | 0.0511 | 5.2669 | 5.4181    |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1