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---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_BERT-1
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. -->
# PhoBERT-Final_Mixed-aug_insert_BERT-1
This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2876
- Accuracy: 0.66
- F1: 0.6737
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8758 | 1.0 | 87 | 0.7479 | 0.67 | 0.6552 |
| 0.5767 | 2.0 | 174 | 0.6555 | 0.74 | 0.7384 |
| 0.4132 | 3.0 | 261 | 0.7503 | 0.75 | 0.7532 |
| 0.2927 | 4.0 | 348 | 0.8208 | 0.68 | 0.6890 |
| 0.2246 | 5.0 | 435 | 1.0222 | 0.68 | 0.6927 |
| 0.1536 | 6.0 | 522 | 1.1675 | 0.67 | 0.6839 |
| 0.1218 | 7.0 | 609 | 1.2362 | 0.66 | 0.6737 |
| 0.1142 | 8.0 | 696 | 1.2876 | 0.66 | 0.6737 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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