---
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: 1.1553

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2947        | 0.13  | 100  | 1.7430          |
| 1.8174        | 0.25  | 200  | 1.3561          |
| 1.5218        | 0.38  | 300  | 1.2409          |
| 1.4277        | 0.51  | 400  | 1.2068          |
| 1.3855        | 0.64  | 500  | 1.1918          |
| 1.3648        | 0.76  | 600  | 1.1808          |
| 1.3438        | 0.89  | 700  | 1.1744          |
| 1.3408        | 1.02  | 800  | 1.1685          |
| 1.3357        | 1.15  | 900  | 1.1658          |
| 1.3258        | 1.27  | 1000 | 1.1620          |
| 1.3187        | 1.4   | 1100 | 1.1597          |
| 1.3195        | 1.53  | 1200 | 1.1577          |
| 1.3168        | 1.65  | 1300 | 1.1572          |
| 1.3167        | 1.78  | 1400 | 1.1559          |
| 1.311         | 1.91  | 1500 | 1.1553          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3