---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: flan_t5_small_twitter
  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_small_twitter

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4985
- Accuracy: 0.7472
- F1 Macro: 0.6954
- F1 Micro: 0.7472

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.5055        | 0.18  | 50   | 0.5210          | 0.7537   | 0.7230   | 0.7537   |
| 0.5045        | 0.37  | 100  | 0.5018          | 0.7445   | 0.6934   | 0.7445   |
| 0.4727        | 0.55  | 150  | 0.5356          | 0.7243   | 0.6002   | 0.7243   |
| 0.4924        | 0.74  | 200  | 0.4985          | 0.7472   | 0.6954   | 0.7472   |
| 0.4847        | 0.92  | 250  | 0.4992          | 0.7528   | 0.7107   | 0.7528   |
| 0.4107        | 1.1   | 300  | 0.5264          | 0.75     | 0.7086   | 0.75     |
| 0.4197        | 1.29  | 350  | 0.5231          | 0.7436   | 0.7126   | 0.7436   |
| 0.4002        | 1.47  | 400  | 0.5312          | 0.7509   | 0.7009   | 0.7509   |
| 0.4381        | 1.65  | 450  | 0.5216          | 0.7482   | 0.7000   | 0.7482   |
| 0.4125        | 1.84  | 500  | 0.5262          | 0.7509   | 0.7161   | 0.7509   |
| 0.3665        | 2.02  | 550  | 0.5205          | 0.7546   | 0.7190   | 0.7546   |
| 0.3855        | 2.21  | 600  | 0.5672          | 0.7537   | 0.7161   | 0.7537   |
| 0.3125        | 2.39  | 650  | 0.5732          | 0.7509   | 0.7066   | 0.7509   |
| 0.2955        | 2.57  | 700  | 0.5928          | 0.7555   | 0.7122   | 0.7555   |
| 0.3556        | 2.76  | 750  | 0.5704          | 0.7537   | 0.7174   | 0.7537   |
| 0.3578        | 2.94  | 800  | 0.5706          | 0.7518   | 0.7069   | 0.7518   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2