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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gpt2-alpaca-instruction-fine-tuning-qlora |
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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-alpaca-instruction-fine-tuning-qlora |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8887 |
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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 and evaluation data |
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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: 0.0005 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.02 | 50 | 2.4375 | |
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| No log | 0.04 | 100 | 2.375 | |
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| No log | 0.06 | 150 | 2.2637 | |
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| No log | 0.08 | 200 | 2.1855 | |
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| No log | 0.1 | 250 | 2.1094 | |
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| No log | 0.12 | 300 | 2.0840 | |
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| No log | 0.14 | 350 | 2.0977 | |
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| No log | 0.16 | 400 | 2.0488 | |
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| No log | 0.18 | 450 | 2.0332 | |
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| No log | 0.2 | 500 | 2.0312 | |
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| No log | 0.22 | 550 | 2.0352 | |
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| No log | 0.24 | 600 | 2.0430 | |
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| No log | 0.26 | 650 | 2.0117 | |
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| No log | 0.28 | 700 | 2.0117 | |
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| No log | 0.3 | 750 | 2.0059 | |
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| No log | 0.32 | 800 | 1.9961 | |
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| No log | 0.34 | 850 | 1.9551 | |
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| No log | 0.36 | 900 | 1.9463 | |
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| No log | 0.38 | 950 | 1.9854 | |
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| 2.4218 | 0.4 | 1000 | 1.9883 | |
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| 2.4218 | 0.42 | 1050 | 1.9766 | |
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| 2.4218 | 0.44 | 1100 | 1.9424 | |
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| 2.4218 | 0.46 | 1150 | 1.9727 | |
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| 2.4218 | 0.48 | 1200 | 1.9473 | |
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| 2.4218 | 0.5 | 1250 | 1.9580 | |
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| 2.4218 | 0.52 | 1300 | 1.9404 | |
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| 2.4218 | 0.54 | 1350 | 1.9287 | |
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| 2.4218 | 0.56 | 1400 | 1.9473 | |
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| 2.4218 | 0.58 | 1450 | 1.9209 | |
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| 2.4218 | 0.6 | 1500 | 1.9219 | |
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| 2.4218 | 0.62 | 1550 | 1.9336 | |
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| 2.4218 | 0.64 | 1600 | 1.9287 | |
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| 2.4218 | 0.66 | 1650 | 1.9082 | |
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| 2.4218 | 0.68 | 1700 | 1.9219 | |
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| 2.4218 | 0.7 | 1750 | 1.8994 | |
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| 2.4218 | 0.72 | 1800 | 1.9092 | |
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| 2.4218 | 0.74 | 1850 | 1.8877 | |
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| 2.4218 | 0.76 | 1900 | 1.8994 | |
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| 2.4218 | 0.78 | 1950 | 1.8955 | |
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| 2.1818 | 0.8 | 2000 | 1.8896 | |
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| 2.1818 | 0.82 | 2050 | 1.8867 | |
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| 2.1818 | 0.84 | 2100 | 1.8857 | |
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| 2.1818 | 0.86 | 2150 | 1.8916 | |
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| 2.1818 | 0.88 | 2200 | 1.8857 | |
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| 2.1818 | 0.9 | 2250 | 1.8916 | |
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| 2.1818 | 0.92 | 2300 | 1.8926 | |
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| 2.1818 | 0.94 | 2350 | 1.8896 | |
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| 2.1818 | 0.96 | 2400 | 1.8887 | |
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| 2.1818 | 0.98 | 2450 | 1.8887 | |
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| 2.1818 | 1.0 | 2500 | 1.8887 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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