| | --- |
| | library_name: peft |
| | license: mit |
| | base_model: gpt2 |
| | tags: |
| | - base_model:adapter:gpt2 |
| | - lora |
| | - transformers |
| | pipeline_tag: text-generation |
| | model-index: |
| | - name: gpt2_lora_instruction |
| | 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. --> |
| |
|
| | # gpt2_lora_instruction |
| |
|
| | This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: nan |
| |
|
| | ## 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: 0.0003 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:------:|:---------------:| |
| | | 1.577 | 1.0 | 10530 | 1.5139 | |
| | | 1.5405 | 2.0 | 21060 | 1.4920 | |
| | | 1.4831 | 3.0 | 31590 | 1.4804 | |
| | | 1.5491 | 4.0 | 42120 | 1.4737 | |
| | | 0.0 | 5.0 | 52650 | nan | |
| | | 0.0 | 6.0 | 63180 | nan | |
| | | 0.0 | 7.0 | 73710 | nan | |
| | | 0.0 | 8.0 | 84240 | nan | |
| | | 0.0 | 9.0 | 94770 | nan | |
| | | 0.0 | 10.0 | 105300 | nan | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.17.1 |
| | - Transformers 4.57.1 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.4.2 |
| | - Tokenizers 0.22.1 |
