---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google/flan-t5-large
model-index:
- name: LoRA-FlanT5-large
  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. -->

# LoRA-FlanT5-large

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co./google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0791

## 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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9842        | 0.24  | 250  | 0.0915          |
| 0.1063        | 0.48  | 500  | 0.0848          |
| 0.1006        | 0.72  | 750  | 0.0823          |
| 0.0991        | 0.96  | 1000 | 0.0812          |
| 0.0979        | 1.2   | 1250 | 0.0805          |
| 0.0966        | 1.44  | 1500 | 0.0801          |
| 0.0946        | 1.69  | 1750 | 0.0798          |
| 0.0965        | 1.93  | 2000 | 0.0797          |
| 0.0964        | 2.17  | 2250 | 0.0795          |
| 0.0953        | 2.41  | 2500 | 0.0794          |
| 0.095         | 2.65  | 2750 | 0.0793          |
| 0.0958        | 2.89  | 3000 | 0.0792          |
| 0.0952        | 3.13  | 3250 | 0.0792          |
| 0.095         | 3.37  | 3500 | 0.0792          |
| 0.0966        | 3.61  | 3750 | 0.0792          |
| 0.0948        | 3.85  | 4000 | 0.0792          |
| 0.0954        | 4.09  | 4250 | 0.0791          |
| 0.0944        | 4.33  | 4500 | 0.0792          |
| 0.0947        | 4.57  | 4750 | 0.0791          |
| 0.0962        | 4.81  | 5000 | 0.0791          |
| 0.0947        | 5.06  | 5250 | 0.0792          |
| 0.0943        | 5.3   | 5500 | 0.0791          |
| 0.0946        | 5.54  | 5750 | 0.0792          |
| 0.0956        | 5.78  | 6000 | 0.0791          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2