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---
license: mit
base_model: wonrax/phobert-base-vietnamese-sentiment
tags:
- generated_from_keras_callback
model-index:
- name: Q317/EmoraBert4
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Q317/EmoraBert4

This model is a fine-tuned version of [wonrax/phobert-base-vietnamese-sentiment](https://huggingface.co/wonrax/phobert-base-vietnamese-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2662
- Validation Loss: 0.8742
- Train Accuracy: 0.7177
- Epoch: 4

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 86940, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.7839     | 0.6986          | 0.6922         | 0     |
| 0.6196     | 0.7086          | 0.7173         | 1     |
| 0.4885     | 0.7005          | 0.7237         | 2     |
| 0.3699     | 0.7995          | 0.7212         | 3     |
| 0.2662     | 0.8742          | 0.7177         | 4     |


### Framework versions

- Transformers 4.33.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3