---
base_model: vinai/bartpho-word-base
tags:
- generated_from_trainer
model-index:
- name: bartpho-word-base-ed-notpl
  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. -->

# bartpho-word-base-ed-notpl

This model is a fine-tuned version of [vinai/bartpho-word-base](https://huggingface.co/vinai/bartpho-word-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0296
- F1 Micro: 0.8132
- Recall Micro: 0.8123
- Precision Micro: 0.8142
- F1 Macro: 0.5908
- Recall Macro: 0.6258
- Precision Macro: 0.5885

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Micro | Recall Micro | Precision Micro | F1 Macro | Recall Macro | Precision Macro |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| No log        | 0.9987 | 393  | 0.0272          | 0.788    | 0.7979       | 0.7783          | 0.4634   | 0.4821       | 0.5358          |
| 0.155         | 2.0    | 787  | 0.0260          | 0.7757   | 0.7633       | 0.7885          | 0.5149   | 0.5538       | 0.5169          |
| 0.0248        | 2.9987 | 1180 | 0.0248          | 0.7874   | 0.7887       | 0.7861          | 0.5407   | 0.5681       | 0.5688          |
| 0.0197        | 4.0    | 1574 | 0.0237          | 0.8067   | 0.8191       | 0.7948          | 0.5628   | 0.5908       | 0.5900          |
| 0.0197        | 4.9987 | 1967 | 0.0240          | 0.8061   | 0.8049       | 0.8073          | 0.5601   | 0.5593       | 0.5880          |
| 0.0158        | 6.0    | 2361 | 0.0269          | 0.7982   | 0.8027       | 0.7937          | 0.5866   | 0.6815       | 0.5364          |
| 0.0121        | 6.9987 | 2754 | 0.0268          | 0.8132   | 0.8123       | 0.8140          | 0.5979   | 0.6077       | 0.6182          |
| 0.0097        | 8.0    | 3148 | 0.0279          | 0.8184   | 0.8200       | 0.8169          | 0.5908   | 0.6050       | 0.6037          |
| 0.0082        | 8.9987 | 3541 | 0.0288          | 0.8129   | 0.8114       | 0.8144          | 0.5895   | 0.6285       | 0.5846          |
| 0.0082        | 9.9873 | 3930 | 0.0296          | 0.8132   | 0.8123       | 0.8142          | 0.5908   | 0.6258       | 0.5885          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1