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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Contract-new-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-new-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: 0.1272
- Accuracy: 0.9628
## 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 | 0.1812 | 0.9386 |
| No log | 2.0 | 498 | 0.1364 | 0.9517 |
| No log | 3.0 | 747 | 0.1272 | 0.9628 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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