---
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: phobert-human-finetune-seg-seed-6960
  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-human-finetune-seg-seed-6960

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:
- Loss: 0.5298
- Accuracy: 0.8578
- Precision: 0.6727
- Recall: 0.6734
- F1: 0.6699

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 346  | 0.4193          | 0.8417   | 0.6207    | 0.6366 | 0.6191 |
| 0.461         | 2.0   | 692  | 0.3603          | 0.8668   | 0.6783    | 0.6527 | 0.6589 |
| 0.2821        | 3.0   | 1038 | 0.4674          | 0.8323   | 0.5692    | 0.5625 | 0.5657 |
| 0.2821        | 4.0   | 1384 | 0.5683          | 0.8675   | 0.7121    | 0.5963 | 0.6240 |
| 0.1664        | 5.0   | 1730 | 0.5298          | 0.8578   | 0.6727    | 0.6734 | 0.6699 |
| 0.1125        | 6.0   | 2076 | 0.6659          | 0.8391   | 0.6285    | 0.6851 | 0.6527 |
| 0.1125        | 7.0   | 2422 | 0.7109          | 0.8634   | 0.6862    | 0.5978 | 0.6292 |
| 0.0863        | 8.0   | 2768 | 0.7702          | 0.8638   | 0.6980    | 0.5886 | 0.6282 |
| 0.0739        | 9.0   | 3114 | 0.6283          | 0.8574   | 0.6609    | 0.6352 | 0.6472 |
| 0.0739        | 10.0  | 3460 | 0.8402          | 0.8537   | 0.6689    | 0.6275 | 0.6441 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0