metadata
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: []
exaone_CSAT_test
This model is a fine-tuned version of 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