---
library_name: peft
tags:
- generated_from_trainer
base_model: slplab/polyglot-ko-1.3b-pretrained-asd
model-index:
- name: pretrain-asd_w-cot_wo-asd_text-features
  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. -->

# pretrain-asd_w-cot_wo-asd_text-features

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2917

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.526         | 0.1727 | 1000  | 0.3186          |
| 0.3076        | 0.3454 | 2000  | 0.3046          |
| 0.3016        | 0.5181 | 3000  | 0.3004          |
| 0.2988        | 0.6908 | 4000  | 0.3006          |
| 0.2964        | 0.8636 | 5000  | 0.2990          |
| 0.2994        | 1.0363 | 6000  | 0.2966          |
| 0.297         | 1.2090 | 7000  | 0.2961          |
| 0.2956        | 1.3817 | 8000  | 0.2953          |
| 0.2919        | 1.5544 | 9000  | 0.2947          |
| 0.2909        | 1.7271 | 10000 | 0.2939          |
| 0.2896        | 1.8998 | 11000 | 0.2939          |
| 0.2958        | 2.0725 | 12000 | 0.2928          |
| 0.2892        | 2.2453 | 13000 | 0.2934          |
| 0.2901        | 2.4180 | 14000 | 0.2926          |
| 0.2899        | 2.5907 | 15000 | 0.2922          |
| 0.2906        | 2.7634 | 16000 | 0.2918          |
| 0.2902        | 2.9361 | 17000 | 0.2917          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1