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--- |
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license: mit |
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base_model: gpt2-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- customized |
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model-index: |
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- name: gpt2-large-lora-sft |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gpt2-large-lora-sft |
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This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the customized dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00013 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 6 |
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- total_train_batch_size: 6 |
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- total_eval_batch_size: 48 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2.5 |
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### Training results |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.3 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Mikivis__gpt2-large-lora-sft) |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | 28.05 | |
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| ARC (25-shot) | 26.79 | |
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| HellaSwag (10-shot) | 44.15 | |
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| MMLU (5-shot) | 25.82 | |
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| TruthfulQA (0-shot) | 39.06 | |
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| Winogrande (5-shot) | 55.09 | |
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| GSM8K (5-shot) | 0.0 | |
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| DROP (3-shot) | 5.46 | |
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