---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: t5_base_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. -->

# t5_base_twitter

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4913
- Accuracy: 0.7656
- F1 Macro: 0.7266
- F1 Micro: 0.7656

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.4808        | 0.18  | 50   | 0.5170          | 0.7445   | 0.6740   | 0.7445   |
| 0.5169        | 0.37  | 100  | 0.5100          | 0.7555   | 0.7269   | 0.7555   |
| 0.4548        | 0.55  | 150  | 0.4922          | 0.7647   | 0.7017   | 0.7647   |
| 0.498         | 0.74  | 200  | 0.5057          | 0.7518   | 0.6776   | 0.7518   |
| 0.4844        | 0.92  | 250  | 0.4913          | 0.7656   | 0.7266   | 0.7656   |
| 0.3949        | 1.1   | 300  | 0.5401          | 0.7482   | 0.6885   | 0.7482   |
| 0.4028        | 1.29  | 350  | 0.5463          | 0.7482   | 0.7209   | 0.7482   |
| 0.3778        | 1.47  | 400  | 0.5438          | 0.7555   | 0.7087   | 0.7555   |
| 0.4383        | 1.65  | 450  | 0.5412          | 0.7381   | 0.7095   | 0.7381   |
| 0.3984        | 1.84  | 500  | 0.5293          | 0.7555   | 0.7239   | 0.7555   |
| 0.3122        | 2.02  | 550  | 0.5272          | 0.7564   | 0.7212   | 0.7564   |
| 0.2764        | 2.21  | 600  | 0.5961          | 0.7463   | 0.7048   | 0.7463   |
| 0.236         | 2.39  | 650  | 0.6630          | 0.7454   | 0.6996   | 0.7454   |
| 0.1996        | 2.57  | 700  | 0.7070          | 0.7482   | 0.6967   | 0.7482   |
| 0.2245        | 2.76  | 750  | 0.6734          | 0.7454   | 0.7016   | 0.7454   |
| 0.2903        | 2.94  | 800  | 0.6760          | 0.7454   | 0.6954   | 0.7454   |


### Framework versions

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