---
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-69
  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-69

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: 0.4456
- Accuracy: 0.8656
- Precision: 0.6916
- Recall: 0.6146
- F1: 0.6460

## 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  | 0.4223          | 0.8458   | 0.6342    | 0.6336 | 0.6232 |
| 0.4575        | 2.0   | 692  | 0.3914          | 0.8574   | 0.6554    | 0.5877 | 0.5935 |
| 0.2895        | 3.0   | 1038 | 0.4456          | 0.8656   | 0.6916    | 0.6146 | 0.6460 |
| 0.2895        | 4.0   | 1384 | 0.5710          | 0.8664   | 0.7133    | 0.5867 | 0.6226 |
| 0.1725        | 5.0   | 1730 | 0.6641          | 0.8585   | 0.6657    | 0.6120 | 0.6354 |
| 0.1259        | 6.0   | 2076 | 0.6784          | 0.8559   | 0.6550    | 0.6223 | 0.6356 |
| 0.1259        | 7.0   | 2422 | 0.5981          | 0.8481   | 0.6358    | 0.6313 | 0.6309 |
| 0.0902        | 8.0   | 2768 | 0.6867          | 0.8331   | 0.6259    | 0.6655 | 0.6343 |


### Framework versions

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