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

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: 0.9867

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.548         | 0.15  | 100  | 1.9606          |
| 2.0409        | 0.29  | 200  | 1.5282          |
| 1.6969        | 0.44  | 300  | 1.2851          |
| 1.4654        | 0.59  | 400  | 1.1794          |
| 1.3643        | 0.73  | 500  | 1.1358          |
| 1.3305        | 0.88  | 600  | 1.1068          |
| 1.2952        | 1.03  | 700  | 1.0873          |
| 1.211         | 1.17  | 800  | 1.0703          |
| 1.2123        | 1.32  | 900  | 1.0590          |
| 1.229         | 1.47  | 1000 | 1.0505          |
| 1.2136        | 1.61  | 1100 | 1.0464          |
| 1.1835        | 1.76  | 1200 | 1.0402          |
| 1.217         | 1.91  | 1300 | 1.0319          |
| 1.1986        | 2.05  | 1400 | 1.0300          |
| 1.1586        | 2.2   | 1500 | 1.0257          |
| 1.1634        | 2.35  | 1600 | 1.0214          |
| 1.1661        | 2.49  | 1700 | 1.0170          |
| 1.166         | 2.64  | 1800 | 1.0157          |
| 1.1663        | 2.79  | 1900 | 1.0126          |
| 1.1367        | 2.93  | 2000 | 1.0107          |
| 1.1576        | 3.08  | 2100 | 1.0100          |
| 1.1314        | 3.23  | 2200 | 1.0070          |
| 1.1198        | 3.37  | 2300 | 1.0049          |
| 1.1712        | 3.52  | 2400 | 1.0019          |
| 1.1369        | 3.67  | 2500 | 1.0028          |
| 1.1604        | 3.82  | 2600 | 1.0005          |
| 1.1101        | 3.96  | 2700 | 0.9977          |
| 1.1227        | 4.11  | 2800 | 0.9968          |
| 1.1247        | 4.26  | 2900 | 0.9963          |
| 1.1211        | 4.4   | 3000 | 0.9952          |
| 1.1398        | 4.55  | 3100 | 0.9939          |
| 1.1333        | 4.7   | 3200 | 0.9928          |
| 1.1367        | 4.84  | 3300 | 0.9918          |
| 1.1124        | 4.99  | 3400 | 0.9919          |
| 1.1298        | 5.14  | 3500 | 0.9905          |
| 1.117         | 5.28  | 3600 | 0.9904          |
| 1.1237        | 5.43  | 3700 | 0.9886          |
| 1.1016        | 5.58  | 3800 | 0.9889          |
| 1.1492        | 5.72  | 3900 | 0.9887          |
| 1.1032        | 5.87  | 4000 | 0.9882          |
| 1.0838        | 6.02  | 4100 | 0.9879          |
| 1.0807        | 6.16  | 4200 | 0.9880          |
| 1.1062        | 6.31  | 4300 | 0.9879          |
| 1.131         | 6.46  | 4400 | 0.9873          |
| 1.1159        | 6.6   | 4500 | 0.9872          |
| 1.1361        | 6.75  | 4600 | 0.9868          |
| 1.1051        | 6.9   | 4700 | 0.9867          |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3