---
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: PhoLexiContent-10304
  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. -->

# PhoLexiContent-10304

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: 0.2676
- Accuracy: 0.9379
- F1: 0.9072
- Precision: 0.9100
- Recall: 0.9046

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7189        | 2.7586  | 100  | 0.1735          | 0.9437   | 0.9157 | 0.9199    | 0.9116 |
| 0.178         | 5.5172  | 200  | 0.1864          | 0.9408   | 0.9099 | 0.9211    | 0.8998 |
| 0.0931        | 8.2759  | 300  | 0.2137          | 0.9418   | 0.9124 | 0.9182    | 0.9070 |
| 0.0931        | 11.0345 | 400  | 0.2234          | 0.9408   | 0.9129 | 0.9096    | 0.9163 |
| 0.0564        | 13.7931 | 500  | 0.2346          | 0.9370   | 0.9075 | 0.9030    | 0.9122 |
| 0.0334        | 16.5517 | 600  | 0.2652          | 0.9350   | 0.9037 | 0.9030    | 0.9044 |
| 0.0334        | 19.3103 | 700  | 0.2676          | 0.9379   | 0.9072 | 0.9100    | 0.9046 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0