|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: EleutherAI/polyglot-ko-1.3b |
|
model-index: |
|
- name: pretrain_w-cot_w-asd |
|
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_w-cot_w-asd |
|
|
|
This model is a fine-tuned version of [EleutherAI/polyglot-ko-1.3b](https://huggingface.co/EleutherAI/polyglot-ko-1.3b) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2650 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:-----:|:---------------:| |
|
| 0.6959 | 0.1725 | 1000 | 0.2915 | |
|
| 0.2871 | 0.3450 | 2000 | 0.2810 | |
|
| 0.2737 | 0.5174 | 3000 | 0.2769 | |
|
| 0.2759 | 0.6899 | 4000 | 0.2737 | |
|
| 0.2708 | 0.8624 | 5000 | 0.2717 | |
|
| 0.2695 | 1.0349 | 6000 | 0.2716 | |
|
| 0.2673 | 1.2074 | 7000 | 0.2713 | |
|
| 0.2697 | 1.3798 | 8000 | 0.2694 | |
|
| 0.2658 | 1.5523 | 9000 | 0.2682 | |
|
| 0.2674 | 1.7248 | 10000 | 0.2673 | |
|
| 0.2641 | 1.8973 | 11000 | 0.2664 | |
|
| 0.2626 | 2.0698 | 12000 | 0.2666 | |
|
| 0.2612 | 2.2422 | 13000 | 0.2662 | |
|
| 0.266 | 2.4147 | 14000 | 0.2655 | |
|
| 0.2626 | 2.5872 | 15000 | 0.2654 | |
|
| 0.2637 | 2.7597 | 16000 | 0.2652 | |
|
| 0.2623 | 2.9322 | 17000 | 0.2650 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.41.1 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
