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

# t5_small_twitter

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4976
- Accuracy: 0.7445
- F1 Macro: 0.6956
- F1 Micro: 0.7445

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.4779        | 0.18  | 50   | 0.5151          | 0.7564   | 0.7177   | 0.7564   |
| 0.5123        | 0.37  | 100  | 0.5060          | 0.7528   | 0.6987   | 0.7528   |
| 0.4617        | 0.55  | 150  | 0.5287          | 0.7270   | 0.6149   | 0.7270   |
| 0.4942        | 0.74  | 200  | 0.4976          | 0.7445   | 0.6956   | 0.7445   |
| 0.4783        | 0.92  | 250  | 0.4978          | 0.7574   | 0.7124   | 0.7574   |
| 0.4369        | 1.1   | 300  | 0.5052          | 0.7601   | 0.7124   | 0.7601   |
| 0.439         | 1.29  | 350  | 0.5092          | 0.7564   | 0.7224   | 0.7564   |
| 0.4417        | 1.47  | 400  | 0.5228          | 0.7546   | 0.6808   | 0.7546   |
| 0.47          | 1.65  | 450  | 0.5087          | 0.7693   | 0.7235   | 0.7693   |
| 0.4415        | 1.84  | 500  | 0.5106          | 0.7647   | 0.7262   | 0.7647   |
| 0.4297        | 2.02  | 550  | 0.5023          | 0.7629   | 0.7291   | 0.7629   |
| 0.4366        | 2.21  | 600  | 0.5225          | 0.7555   | 0.7127   | 0.7555   |
| 0.3623        | 2.39  | 650  | 0.5226          | 0.7583   | 0.7157   | 0.7583   |
| 0.3337        | 2.57  | 700  | 0.5313          | 0.7574   | 0.7144   | 0.7574   |
| 0.4158        | 2.76  | 750  | 0.5385          | 0.7601   | 0.7211   | 0.7601   |
| 0.4003        | 2.94  | 800  | 0.5350          | 0.7546   | 0.7058   | 0.7546   |


### Framework versions

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