---
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-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-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: 0.4071
- Accuracy: 0.8641
- Precision: 0.6832
- Recall: 0.6493
- F1: 0.6626

## 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  | 0.3907          | 0.8612   | 0.6775    | 0.6062 | 0.6331 |
| 0.4561        | 2.0   | 692  | 0.3802          | 0.8544   | 0.6457    | 0.6216 | 0.6237 |
| 0.2919        | 3.0   | 1038 | 0.4071          | 0.8641   | 0.6832    | 0.6493 | 0.6626 |
| 0.2919        | 4.0   | 1384 | 0.5535          | 0.8634   | 0.7034    | 0.5859 | 0.6197 |
| 0.1808        | 5.0   | 1730 | 0.6397          | 0.8372   | 0.6556    | 0.6194 | 0.6087 |
| 0.1251        | 6.0   | 2076 | 0.5417          | 0.8570   | 0.6550    | 0.6391 | 0.6467 |
| 0.1251        | 7.0   | 2422 | 0.6166          | 0.8608   | 0.6760    | 0.6321 | 0.6509 |
| 0.0932        | 8.0   | 2768 | 0.7020          | 0.8368   | 0.6254    | 0.6824 | 0.6496 |


### Framework versions

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