peft tensorboard safetensors generated_from_trainer base_model:google/flan-t5-base base_model:adapter:google/flan-t5-base license:apache-2.0 region:us
---
base_model: google/flan-t5-base
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: NDC_summarization_peft_v1
  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. -->

# NDC_summarization_peft_v1

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0798

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1069        | 0.08  | 100  | 0.1004          |
| 0.1044        | 0.16  | 200  | 0.0972          |
| 0.0954        | 0.24  | 300  | 0.0943          |
| 0.1288        | 0.32  | 400  | 0.1012          |
| 0.1099        | 0.4   | 500  | 0.0950          |
| 0.1046        | 0.48  | 600  | 0.0949          |
| 0.1024        | 0.56  | 700  | 0.0926          |
| 0.1049        | 0.64  | 800  | 0.0929          |
| 0.1028        | 0.72  | 900  | 0.0915          |
| 0.1062        | 0.8   | 1000 | 0.0902          |
| 0.1068        | 0.88  | 1100 | 0.0903          |
| 0.1076        | 0.97  | 1200 | 0.0900          |
| 0.1001        | 1.05  | 1300 | 0.0889          |
| 0.0972        | 1.13  | 1400 | 0.0881          |
| 0.0988        | 1.21  | 1500 | 0.0880          |
| 0.0987        | 1.29  | 1600 | 0.0870          |
| 0.092         | 1.37  | 1700 | 0.0882          |
| 0.0946        | 1.45  | 1800 | 0.0862          |
| 0.0938        | 1.53  | 1900 | 0.0882          |
| 0.0939        | 1.61  | 2000 | 0.0868          |
| 0.1012        | 1.69  | 2100 | 0.0863          |
| 0.0927        | 1.77  | 2200 | 0.0856          |
| 0.0982        | 1.85  | 2300 | 0.0851          |
| 0.1021        | 1.93  | 2400 | 0.0860          |
| 0.094         | 2.01  | 2500 | 0.0845          |
| 0.094         | 2.09  | 2600 | 0.0856          |
| 0.0946        | 2.17  | 2700 | 0.0852          |
| 0.0944        | 2.25  | 2800 | 0.0863          |
| 0.0911        | 2.33  | 2900 | 0.0859          |
| 0.0945        | 2.41  | 3000 | 0.0846          |
| 0.0928        | 2.49  | 3100 | 0.0845          |
| 0.0909        | 2.57  | 3200 | 0.0835          |
| 0.0882        | 2.65  | 3300 | 0.0834          |
| 0.0891        | 2.74  | 3400 | 0.0830          |
| 0.0875        | 2.82  | 3500 | 0.0829          |
| 0.0886        | 2.9   | 3600 | 0.0834          |
| 0.0902        | 2.98  | 3700 | 0.0825          |
| 0.0922        | 3.06  | 3800 | 0.0838          |
| 0.0846        | 3.14  | 3900 | 0.0833          |
| 0.0868        | 3.22  | 4000 | 0.0832          |
| 0.0909        | 3.3   | 4100 | 0.0825          |
| 0.0873        | 3.38  | 4200 | 0.0830          |
| 0.0881        | 3.46  | 4300 | 0.0834          |
| 0.0896        | 3.54  | 4400 | 0.0818          |
| 0.0862        | 3.62  | 4500 | 0.0828          |
| 0.0857        | 3.7   | 4600 | 0.0820          |
| 0.0867        | 3.78  | 4700 | 0.0814          |
| 0.0867        | 3.86  | 4800 | 0.0822          |
| 0.0892        | 3.94  | 4900 | 0.0818          |
| 0.0889        | 4.02  | 5000 | 0.0813          |
| 0.0851        | 4.1   | 5100 | 0.0816          |
| 0.0911        | 4.18  | 5200 | 0.0807          |
| 0.0864        | 4.26  | 5300 | 0.0813          |
| 0.0838        | 4.34  | 5400 | 0.0823          |
| 0.0844        | 4.42  | 5500 | 0.0815          |
| 0.0876        | 4.51  | 5600 | 0.0808          |
| 0.0859        | 4.59  | 5700 | 0.0808          |
| 0.082         | 4.67  | 5800 | 0.0802          |
| 0.0829        | 4.75  | 5900 | 0.0813          |
| 0.0838        | 4.83  | 6000 | 0.0806          |
| 0.0843        | 4.91  | 6100 | 0.0806          |
| 0.0907        | 4.99  | 6200 | 0.0808          |
| 0.0806        | 5.07  | 6300 | 0.0808          |
| 0.0832        | 5.15  | 6400 | 0.0806          |
| 0.0915        | 5.23  | 6500 | 0.0813          |
| 0.0822        | 5.31  | 6600 | 0.0811          |
| 0.0869        | 5.39  | 6700 | 0.0799          |
| 0.0877        | 5.47  | 6800 | 0.0806          |
| 0.0832        | 5.55  | 6900 | 0.0805          |
| 0.0867        | 5.63  | 7000 | 0.0809          |
| 0.0825        | 5.71  | 7100 | 0.0800          |
| 0.0816        | 5.79  | 7200 | 0.0804          |
| 0.0822        | 5.87  | 7300 | 0.0802          |
| 0.0792        | 5.95  | 7400 | 0.0800          |
| 0.0834        | 6.03  | 7500 | 0.0809          |
| 0.0831        | 6.11  | 7600 | 0.0801          |
| 0.0842        | 6.19  | 7700 | 0.0807          |
| 0.0829        | 6.28  | 7800 | 0.0803          |
| 0.0835        | 6.36  | 7900 | 0.0804          |
| 0.0843        | 6.44  | 8000 | 0.0802          |
| 0.0798        | 6.52  | 8100 | 0.0803          |
| 0.0827        | 6.6   | 8200 | 0.0805          |
| 0.0859        | 6.68  | 8300 | 0.0796          |
| 0.0803        | 6.76  | 8400 | 0.0797          |
| 0.0889        | 6.84  | 8500 | 0.0802          |
| 0.0848        | 6.92  | 8600 | 0.0803          |
| 0.0762        | 7.0   | 8700 | 0.0801          |
| 0.0837        | 7.08  | 8800 | 0.0795          |
| 0.0876        | 7.16  | 8900 | 0.0799          |
| 0.0844        | 7.24  | 9000 | 0.0800          |
| 0.0793        | 7.32  | 9100 | 0.0799          |
| 0.0799        | 7.4   | 9200 | 0.0799          |
| 0.0832        | 7.48  | 9300 | 0.0798          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2