---
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-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-finetune-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: 0.7113
- Accuracy: 0.8578
- Precision: 0.6561
- Recall: 0.6715
- F1: 0.6635

## 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  | 0.4059          | 0.8503   | 0.6647    | 0.5987 | 0.5996 |
| 0.4526        | 2.0   | 692  | 0.3766          | 0.8623   | 0.6736    | 0.6070 | 0.6324 |
| 0.2959        | 3.0   | 1038 | 0.4422          | 0.8705   | 0.7189    | 0.6002 | 0.6446 |
| 0.2959        | 4.0   | 1384 | 0.5210          | 0.8641   | 0.6842    | 0.6093 | 0.6351 |
| 0.1828        | 5.0   | 1730 | 0.6763          | 0.8376   | 0.6244    | 0.5879 | 0.5898 |
| 0.1244        | 6.0   | 2076 | 0.6496          | 0.8439   | 0.6431    | 0.6854 | 0.6595 |
| 0.1244        | 7.0   | 2422 | 0.6891          | 0.8582   | 0.6621    | 0.6294 | 0.6444 |
| 0.0898        | 8.0   | 2768 | 0.5961          | 0.8544   | 0.6481    | 0.6268 | 0.6368 |
| 0.0719        | 9.0   | 3114 | 0.7113          | 0.8578   | 0.6561    | 0.6715 | 0.6635 |
| 0.0719        | 10.0  | 3460 | 0.8041          | 0.8507   | 0.6407    | 0.6516 | 0.6450 |
| 0.0634        | 11.0  | 3806 | 0.8648          | 0.8638   | 0.6826    | 0.6394 | 0.6560 |
| 0.0566        | 12.0  | 4152 | 0.7883          | 0.8529   | 0.6554    | 0.6632 | 0.6530 |
| 0.0566        | 13.0  | 4498 | 0.8817          | 0.8626   | 0.6879    | 0.6220 | 0.6495 |
| 0.0455        | 14.0  | 4844 | 0.8372          | 0.8548   | 0.6582    | 0.6316 | 0.6439 |


### Framework versions

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