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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: fresh-2-layer-qasc5000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa |
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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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# fresh-2-layer-qasc5000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 14.9541 |
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- Accuracy: 0.4949 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 321 |
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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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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.64 | 100 | 14.0782 | 0.3131 | |
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| No log | 1.27 | 200 | 15.6534 | 0.4596 | |
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| No log | 1.91 | 300 | 16.2410 | 0.4293 | |
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| No log | 2.55 | 400 | 14.4394 | 0.4495 | |
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| 1.861 | 3.18 | 500 | 15.1088 | 0.4646 | |
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| 1.861 | 3.82 | 600 | 14.4621 | 0.4848 | |
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| 1.861 | 4.46 | 700 | 15.0037 | 0.4596 | |
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| 1.861 | 5.1 | 800 | 15.6656 | 0.4293 | |
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| 1.861 | 5.73 | 900 | 15.1955 | 0.4343 | |
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| 0.2711 | 6.37 | 1000 | 14.9541 | 0.4949 | |
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| 0.2711 | 7.01 | 1100 | 14.5891 | 0.4646 | |
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| 0.2711 | 7.64 | 1200 | 15.4136 | 0.4747 | |
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| 0.2711 | 8.28 | 1300 | 15.4486 | 0.4697 | |
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| 0.2711 | 8.92 | 1400 | 14.5015 | 0.4848 | |
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| 0.1568 | 9.55 | 1500 | 14.2260 | 0.4545 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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