---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Contract-base-tokenizer-mDeBERTa-v3-kor-further
  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. -->

# Contract-base-tokenizer-mDeBERTa-v3-kor-further

This model is a fine-tuned version of [lighthouse/mdeberta-v3-base-kor-further](https://huggingface.co/lighthouse/mdeberta-v3-base-kor-further) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0437
- Accuracy: 0.9909

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 249  | 0.0691          | 0.9829   |
| No log        | 2.0   | 498  | 0.0375          | 0.9920   |
| No log        | 3.0   | 747  | 0.0437          | 0.9909   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2