|
--- |
|
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 |