---
library_name: peft
license: other
base_model: LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: exaone_CSAT_test
  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. -->

# exaone_CSAT_test

This model is a fine-tuned version of [LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4792
- Accuracy: 0.5628
- F1: 0.5965

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- training_steps: 2100

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 24.6602       | 0.1121 | 50   | 24.1094         | 0.5477   | 0.5761 |
| 12.8586       | 0.2242 | 100  | 6.5703          | 0.5729   | 0.6062 |
| 0.3657        | 0.3363 | 150  | 0.4956          | 0.5678   | 0.6005 |
| 0.5527        | 0.4484 | 200  | 0.4880          | 0.5678   | 0.6005 |
| 0.9587        | 0.5605 | 250  | 0.5098          | 0.5729   | 0.6054 |
| 0.9119        | 0.6726 | 300  | 0.4468          | 0.5678   | 0.6016 |
| 0.0989        | 0.7848 | 350  | 0.4690          | 0.5729   | 0.6066 |
| 0.6981        | 0.8969 | 400  | 0.4612          | 0.5628   | 0.5965 |
| 0.5197        | 1.0090 | 450  | 0.4792          | 0.5628   | 0.5965 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3