---
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-1337
  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-1337

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: 0.4395
- Accuracy: 0.8570
- Precision: 0.6569
- Recall: 0.6924
- F1: 0.6729

## 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  | 0.3643          | 0.8671   | 0.7013    | 0.5922 | 0.6310 |
| 0.4458        | 2.0   | 692  | 0.3549          | 0.8698   | 0.7011    | 0.6338 | 0.6625 |
| 0.2752        | 3.0   | 1038 | 0.4395          | 0.8570   | 0.6569    | 0.6924 | 0.6729 |
| 0.2752        | 4.0   | 1384 | 0.5660          | 0.8645   | 0.6781    | 0.6046 | 0.6348 |
| 0.1612        | 5.0   | 1730 | 0.6182          | 0.8230   | 0.6101    | 0.6878 | 0.6360 |
| 0.1187        | 6.0   | 2076 | 0.5680          | 0.8679   | 0.6855    | 0.6337 | 0.6545 |
| 0.1187        | 7.0   | 2422 | 0.7394          | 0.8664   | 0.6868    | 0.6266 | 0.6520 |
| 0.0864        | 8.0   | 2768 | 0.6227          | 0.8604   | 0.6723    | 0.6441 | 0.6559 |


### Framework versions

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