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---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
datasets:
- race
model-index:
- name: flan-small-mc-question-options-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. -->

# flan-small-mc-question-options-generation

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on the race dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5747

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3811        | 0.07  | 100  | 2.4007          |
| 2.5622        | 0.15  | 200  | 2.0431          |
| 2.2498        | 0.22  | 300  | 1.9139          |
| 2.1136        | 0.29  | 400  | 1.8218          |
| 2.0392        | 0.36  | 500  | 1.7739          |
| 1.9984        | 0.44  | 600  | 1.7237          |
| 1.9519        | 0.51  | 700  | 1.7058          |
| 1.928         | 0.58  | 800  | 1.6900          |
| 1.9075        | 0.66  | 900  | 1.6687          |
| 1.8968        | 0.73  | 1000 | 1.6631          |
| 1.8758        | 0.8   | 1100 | 1.6519          |
| 1.8863        | 0.87  | 1200 | 1.6431          |
| 1.869         | 0.95  | 1300 | 1.6409          |
| 1.8483        | 1.02  | 1400 | 1.6313          |
| 1.8344        | 1.09  | 1500 | 1.6279          |
| 1.8398        | 1.17  | 1600 | 1.6183          |
| 1.8247        | 1.24  | 1700 | 1.6223          |
| 1.8131        | 1.31  | 1800 | 1.6072          |
| 1.8024        | 1.38  | 1900 | 1.6096          |
| 1.8038        | 1.46  | 2000 | 1.6056          |
| 1.8051        | 1.53  | 2100 | 1.6030          |
| 1.7875        | 1.6   | 2200 | 1.6008          |
| 1.7983        | 1.68  | 2300 | 1.5923          |
| 1.7922        | 1.75  | 2400 | 1.5917          |
| 1.7892        | 1.82  | 2500 | 1.5903          |
| 1.784         | 1.89  | 2600 | 1.5891          |
| 1.7844        | 1.97  | 2700 | 1.5867          |
| 1.7678        | 2.04  | 2800 | 1.5837          |
| 1.7558        | 2.11  | 2900 | 1.5826          |
| 1.7702        | 2.19  | 3000 | 1.5820          |
| 1.7669        | 2.26  | 3100 | 1.5802          |
| 1.7715        | 2.33  | 3200 | 1.5763          |
| 1.7724        | 2.4   | 3300 | 1.5799          |
| 1.757         | 2.48  | 3400 | 1.5783          |
| 1.7648        | 2.55  | 3500 | 1.5763          |
| 1.7691        | 2.62  | 3600 | 1.5772          |
| 1.7607        | 2.69  | 3700 | 1.5758          |
| 1.7574        | 2.77  | 3800 | 1.5745          |
| 1.7586        | 2.84  | 3900 | 1.5748          |
| 1.7583        | 2.91  | 4000 | 1.5745          |
| 1.7611        | 2.99  | 4100 | 1.5747          |


### Framework versions

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