---
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: phobert-human-tl-seed-6969
  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-tl-seed-6969

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: 0.4535
- Accuracy: 0.8387
- Precision: 0.6438
- Recall: 0.4677
- F1: 0.4914

## 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  | 0.5154          | 0.8241   | 0.5456    | 0.3492 | 0.3314 |
| 0.5778        | 2.0   | 692  | 0.4712          | 0.8305   | 0.6220    | 0.4062 | 0.4191 |
| 0.4667        | 3.0   | 1038 | 0.4650          | 0.8331   | 0.6490    | 0.4069 | 0.4227 |
| 0.4667        | 4.0   | 1384 | 0.4665          | 0.8365   | 0.6819    | 0.4147 | 0.4337 |
| 0.4617        | 5.0   | 1730 | 0.4639          | 0.8357   | 0.6591    | 0.4129 | 0.4337 |
| 0.4577        | 6.0   | 2076 | 0.4606          | 0.8368   | 0.6775    | 0.4282 | 0.4479 |
| 0.4577        | 7.0   | 2422 | 0.4626          | 0.8361   | 0.6851    | 0.4134 | 0.4359 |
| 0.4554        | 8.0   | 2768 | 0.4530          | 0.8394   | 0.6468    | 0.4436 | 0.4674 |
| 0.4545        | 9.0   | 3114 | 0.4599          | 0.8342   | 0.6459    | 0.4083 | 0.4288 |
| 0.4545        | 10.0  | 3460 | 0.4603          | 0.8350   | 0.6825    | 0.4375 | 0.4543 |
| 0.4587        | 11.0  | 3806 | 0.4594          | 0.8346   | 0.6499    | 0.4092 | 0.4321 |
| 0.4491        | 12.0  | 4152 | 0.4535          | 0.8387   | 0.6438    | 0.4677 | 0.4914 |
| 0.4491        | 13.0  | 4498 | 0.4555          | 0.8353   | 0.6372    | 0.4213 | 0.4475 |
| 0.4579        | 14.0  | 4844 | 0.4563          | 0.8357   | 0.6552    | 0.4129 | 0.4359 |
| 0.4488        | 15.0  | 5190 | 0.4595          | 0.8335   | 0.6553    | 0.4019 | 0.4217 |
| 0.4587        | 16.0  | 5536 | 0.4663          | 0.8327   | 0.6580    | 0.3987 | 0.4161 |
| 0.4587        | 17.0  | 5882 | 0.4515          | 0.8387   | 0.6235    | 0.4357 | 0.4612 |


### Framework versions

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