metadata
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: []
pipeline_tag: text2text-generation
inference:
parameters:
max_length: 256
num_beams: 4
length_penalty: 1.5
no_repeat_ngram_size: 3
early_stopping: true
peft-flan-t5-mc-question-generation-eduqg
This model is a fine-tuned version of 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