---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FLAN-T5_GLUE_finetuning_lr3e-4
  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-T5_GLUE_finetuning_lr3e-4

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: 0.0936
- Accuracy: 0.8849

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1314        | 0.17  | 2500  | 0.1069          | 0.8312   |
| 0.1087        | 0.34  | 5000  | 0.0960          | 0.8513   |
| 0.1029        | 0.51  | 7500  | 0.0913          | 0.8543   |
| 0.1007        | 0.68  | 10000 | 0.0890          | 0.8587   |
| 0.0961        | 0.85  | 12500 | 0.0870          | 0.865    |
| 0.0933        | 1.02  | 15000 | 0.0875          | 0.8644   |
| 0.0777        | 1.18  | 17500 | 0.0844          | 0.869    |
| 0.0784        | 1.35  | 20000 | 0.0843          | 0.8701   |
| 0.078         | 1.52  | 22500 | 0.0827          | 0.8712   |
| 0.0775        | 1.69  | 25000 | 0.0841          | 0.8711   |
| 0.0774        | 1.86  | 27500 | 0.0824          | 0.8737   |
| 0.0732        | 2.03  | 30000 | 0.0862          | 0.8727   |
| 0.0591        | 2.2   | 32500 | 0.0842          | 0.8766   |
| 0.06          | 2.37  | 35000 | 0.0858          | 0.8762   |
| 0.0595        | 2.54  | 37500 | 0.0843          | 0.8781   |
| 0.061         | 2.71  | 40000 | 0.0818          | 0.88     |
| 0.0598        | 2.88  | 42500 | 0.0813          | 0.8803   |
| 0.0558        | 3.05  | 45000 | 0.0896          | 0.8805   |
| 0.0448        | 3.22  | 47500 | 0.0885          | 0.881    |
| 0.0451        | 3.38  | 50000 | 0.0888          | 0.8805   |
| 0.0449        | 3.55  | 52500 | 0.0873          | 0.882    |
| 0.0457        | 3.72  | 55000 | 0.0853          | 0.8839   |
| 0.0456        | 3.89  | 57500 | 0.0856          | 0.8835   |
| 0.0413        | 4.06  | 60000 | 0.0931          | 0.8828   |
| 0.0342        | 4.23  | 62500 | 0.0961          | 0.8851   |
| 0.0348        | 4.4   | 65000 | 0.0945          | 0.8851   |
| 0.0351        | 4.57  | 67500 | 0.0936          | 0.8845   |
| 0.0346        | 4.74  | 70000 | 0.0940          | 0.8846   |
| 0.0347        | 4.91  | 72500 | 0.0936          | 0.8849   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0+cu117
- Datasets 2.10.1
- Tokenizers 0.12.1