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---
tags:
- generated_from_keras_callback
model-index:
- name: dung1308/RM_system_not_mixed__NLP_model
  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. -->

# dung1308/RM_system_not_mixed__NLP_model

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 4.2670
- Validation Loss: 4.3108
- Epoch: 12

## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -517, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 5.4281     | 4.6304          | 0     |
| 4.5092     | 4.2831          | 1     |
| 4.2234     | 4.2641          | 2     |
| 4.2383     | 4.3122          | 3     |
| 4.2406     | 4.2459          | 4     |
| 4.2113     | 4.2687          | 5     |
| 4.2721     | 4.2425          | 6     |
| 4.3064     | 4.2370          | 7     |
| 4.2685     | 4.2999          | 8     |
| 4.3104     | nan             | 9     |
| 4.2444     | 4.2957          | 10    |
| 4.2041     | 4.2465          | 11    |
| 4.2670     | 4.3108          | 12    |


### Framework versions

- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2