gpt2-large-lora-sft
This model is a fine-tuned version of gpt2-large on the customized dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.00013
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- total_train_batch_size: 6
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.5
Training results
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 28.05 |
| ARC (25-shot) | 26.79 |
| HellaSwag (10-shot) | 44.15 |
| MMLU (5-shot) | 25.82 |
| TruthfulQA (0-shot) | 39.06 |
| Winogrande (5-shot) | 55.09 |
| GSM8K (5-shot) | 0.0 |
| DROP (3-shot) | 5.46 |