---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
model-index:
- name: peft-finetune-flan-t5-mc-question-generation
  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-finetune-flan-t5-mc-question-generation

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: 1.2240

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3143        | 0.13  | 100  | 1.7677          |
| 1.8538        | 0.25  | 200  | 1.4179          |
| 1.5767        | 0.38  | 300  | 1.3186          |
| 1.4908        | 0.51  | 400  | 1.2879          |
| 1.4503        | 0.64  | 500  | 1.2700          |
| 1.4281        | 0.76  | 600  | 1.2578          |
| 1.406         | 0.89  | 700  | 1.2489          |
| 1.4052        | 1.02  | 800  | 1.2415          |
| 1.3974        | 1.15  | 900  | 1.2387          |
| 1.3889        | 1.27  | 1000 | 1.2334          |
| 1.3811        | 1.4   | 1100 | 1.2303          |
| 1.3808        | 1.53  | 1200 | 1.2266          |
| 1.3782        | 1.65  | 1300 | 1.2265          |
| 1.376         | 1.78  | 1400 | 1.2248          |
| 1.3734        | 1.91  | 1500 | 1.2240          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3