metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- gsm8k
model-index:
- name: flan-t5-base-finetuned-gsm8k
results: []
widget:
- text: >-
Please, answer the following question reasoning step-by-step: Manu bought
4 apples and lost one in the market. How many apples does Manu have?
flan-t5-base-finetuned-gsm8k
This model is a fine-tuned version of google/flan-t5-base on the gsm8k dataset. It achieves the following results on the evaluation set:
- Loss: 0.3652
- Rouge2 Precision: 0.3914
- Rouge2 Recall: 0.0816
- Rouge2 Fmeasure: 0.1308
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.425 | 1.0 | 1869 | 0.3942 | 0.3707 | 0.0774 | 0.1238 |
| 0.3849 | 2.0 | 3738 | 0.3769 | 0.3809 | 0.0795 | 0.1272 |
| 0.3663 | 3.0 | 5607 | 0.3698 | 0.3808 | 0.0805 | 0.1285 |
| 0.3553 | 4.0 | 7476 | 0.3659 | 0.3863 | 0.0805 | 0.129 |
| 0.3421 | 5.0 | 9345 | 0.3652 | 0.3914 | 0.0816 | 0.1308 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2