---
base_model: NlpHUST/t5-en-vi-small
tags:
- generated_from_keras_callback
model-index:
- name: Thangnv/t5
  results: []
---

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probably proofread and complete it, then remove this comment. -->

# Thangnv/t5

This model is a fine-tuned version of [NlpHUST/t5-en-vi-small](https://huggingface.co/NlpHUST/t5-en-vi-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7069
- Train Sparse Categorical Accuracy: 0.8147
- Validation Loss: 0.6927
- Validation Sparse Categorical Accuracy: 0.8199
- Epoch: 2

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.8162     | 0.7924                            | 0.7433          | 0.8094                                 | 0     |
| 0.7413     | 0.8077                            | 0.7142          | 0.8151                                 | 1     |
| 0.7069     | 0.8147                            | 0.6927          | 0.8199                                 | 2     |


### Framework versions

- Transformers 4.33.2
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3