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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_w2v
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_w2v
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: 1.1056
- Accuracy: 0.73
- F1: 0.7280
## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8961 | 1.0 | 86 | 0.7149 | 0.69 | 0.6676 |
| 0.5695 | 2.0 | 172 | 0.7188 | 0.71 | 0.7029 |
| 0.3772 | 3.0 | 258 | 0.7802 | 0.71 | 0.7061 |
| 0.2899 | 4.0 | 344 | 0.7639 | 0.76 | 0.7595 |
| 0.2145 | 5.0 | 430 | 0.9140 | 0.73 | 0.7286 |
| 0.1299 | 6.0 | 516 | 1.0655 | 0.72 | 0.7123 |
| 0.1047 | 7.0 | 602 | 1.0912 | 0.73 | 0.7244 |
| 0.0864 | 8.0 | 688 | 1.1056 | 0.73 | 0.7280 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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