---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
model-index:
- name: question_extractor
  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. -->

# question_extractor

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0926

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7133        | 0.0973 | 500   | 0.2155          |
| 0.1448        | 0.1945 | 1000  | 0.1211          |
| 0.1325        | 0.2918 | 1500  | 0.1143          |
| 0.1338        | 0.3890 | 2000  | 0.1098          |
| 0.1256        | 0.4863 | 2500  | 0.1073          |
| 0.1259        | 0.5835 | 3000  | 0.1051          |
| 0.1238        | 0.6808 | 3500  | 0.1034          |
| 0.1188        | 0.7781 | 4000  | 0.1025          |
| 0.1157        | 0.8753 | 4500  | 0.1007          |
| 0.1187        | 0.9726 | 5000  | 0.0998          |
| 0.1135        | 1.0698 | 5500  | 0.0990          |
| 0.1114        | 1.1671 | 6000  | 0.0985          |
| 0.1141        | 1.2643 | 6500  | 0.0973          |
| 0.1106        | 1.3616 | 7000  | 0.0969          |
| 0.1119        | 1.4589 | 7500  | 0.0962          |
| 0.1126        | 1.5561 | 8000  | 0.0961          |
| 0.1076        | 1.6534 | 8500  | 0.0955          |
| 0.1113        | 1.7506 | 9000  | 0.0951          |
| 0.1097        | 1.8479 | 9500  | 0.0947          |
| 0.1098        | 1.9451 | 10000 | 0.0943          |
| 0.1082        | 2.0424 | 10500 | 0.0941          |
| 0.1079        | 2.1397 | 11000 | 0.0939          |
| 0.1056        | 2.2369 | 11500 | 0.0938          |
| 0.1064        | 2.3342 | 12000 | 0.0936          |
| 0.1053        | 2.4314 | 12500 | 0.0933          |
| 0.1085        | 2.5287 | 13000 | 0.0931          |
| 0.1062        | 2.6259 | 13500 | 0.0931          |
| 0.1094        | 2.7232 | 14000 | 0.0929          |
| 0.1081        | 2.8205 | 14500 | 0.0930          |
| 0.1051        | 2.9177 | 15000 | 0.0930          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1