---
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: []
pipeline_tag: text2text-generation
inference:
  parameters:
      max_length: 256
      num_beams: 4
      length_penalty: 1.5
      no_repeat_ngram_size: 3
      early_stopping: True
---

<!-- 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: 1.1306

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2907        | 0.13  | 100  | 1.7315          |
| 1.8012        | 0.25  | 200  | 1.3366          |
| 1.5077        | 0.38  | 300  | 1.2346          |
| 1.419         | 0.51  | 400  | 1.2027          |
| 1.3772        | 0.64  | 500  | 1.1884          |
| 1.3566        | 0.76  | 600  | 1.1770          |
| 1.3348        | 0.89  | 700  | 1.1696          |
| 1.3307        | 1.02  | 800  | 1.1624          |
| 1.3247        | 1.15  | 900  | 1.1586          |
| 1.3139        | 1.27  | 1000 | 1.1537          |
| 1.3048        | 1.4   | 1100 | 1.1507          |
| 1.3045        | 1.53  | 1200 | 1.1476          |
| 1.2999        | 1.65  | 1300 | 1.1451          |
| 1.2978        | 1.78  | 1400 | 1.1425          |
| 1.2903        | 1.91  | 1500 | 1.1407          |
| 1.2897        | 2.04  | 1600 | 1.1409          |
| 1.2881        | 2.16  | 1700 | 1.1386          |
| 1.2845        | 2.29  | 1800 | 1.1374          |
| 1.2749        | 2.42  | 1900 | 1.1360          |
| 1.2846        | 2.55  | 2000 | 1.1349          |
| 1.281         | 2.67  | 2100 | 1.1339          |
| 1.282         | 2.8   | 2200 | 1.1331          |
| 1.2786        | 2.93  | 2300 | 1.1326          |
| 1.2799        | 3.06  | 2400 | 1.1322          |
| 1.2777        | 3.18  | 2500 | 1.1320          |
| 1.2767        | 3.31  | 2600 | 1.1316          |
| 1.2716        | 3.44  | 2700 | 1.1313          |
| 1.2762        | 3.56  | 2800 | 1.1309          |
| 1.2723        | 3.69  | 2900 | 1.1305          |
| 1.2741        | 3.82  | 3000 | 1.1304          |
| 1.2762        | 3.95  | 3100 | 1.1306          |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3