---
library_name: transformers
license: apache-2.0
base_model: team-lucid/hubert-base-korean
tags:
- generated_from_trainer
model-index:
- name: for_test13
  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. -->

# for_test13

This model is a fine-tuned version of [team-lucid/hubert-base-korean](https://huggingface.co/team-lucid/hubert-base-korean) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 9.0800
- Per: 0.8663
- Learning Rate: 0.0000

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use 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: 20
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Per    | Rate   |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 9.8433        | 1.0417 | 50   | 10.8927         | 1.9730 | 0.0001 |
| 6.2994        | 2.0833 | 100  | 10.1801         | 1.4889 | 0.0001 |
| 5.6979        | 3.125  | 150  | 9.8748          | 1.1627 | 0.0001 |
| 5.5696        | 4.1667 | 200  | 9.6279          | 0.9856 | 0.0001 |
| 5.5354        | 5.2083 | 250  | 9.4447          | 0.9282 | 0.0001 |
| 5.3749        | 6.25   | 300  | 9.3013          | 0.8952 | 4e-05  |
| 5.6517        | 7.2917 | 350  | 9.1784          | 0.8771 | 0.0000 |
| 5.1293        | 8.3333 | 400  | 9.0618          | 0.8661 | 0.0000 |
| 5.5912        | 9.375  | 450  | 9.0800          | 0.8663 | 0.0000 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3