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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-mmlu_EVAL_mmlu |
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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-mmlu_EVAL_mmlu |
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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: 0.0196 |
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- Accuracy: 0.9942 |
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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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- num_epochs: 20 |
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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 | 1.0 | 439 | 1.1960 | 0.518 | |
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| 1.2946 | 2.0 | 878 | 0.9728 | 0.61 | |
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| 1.1382 | 3.0 | 1317 | 0.6014 | 0.796 | |
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| 0.8904 | 4.0 | 1756 | 0.3594 | 0.88 | |
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| 0.5997 | 5.0 | 2195 | 0.2266 | 0.932 | |
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| 0.413 | 6.0 | 2634 | 0.1883 | 0.936 | |
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| 0.2801 | 7.0 | 3073 | 0.1547 | 0.95 | |
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| 0.2194 | 8.0 | 3512 | 0.1150 | 0.952 | |
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| 0.2194 | 9.0 | 3951 | 0.0860 | 0.974 | |
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| 0.1697 | 10.0 | 4390 | 0.0870 | 0.974 | |
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| 0.134 | 11.0 | 4829 | 0.0561 | 0.98 | |
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| 0.1098 | 12.0 | 5268 | 0.0450 | 0.99 | |
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| 0.0908 | 13.0 | 5707 | 0.0301 | 0.988 | |
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| 0.0771 | 14.0 | 6146 | 0.0229 | 0.992 | |
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| 0.0618 | 15.0 | 6585 | 0.0174 | 0.996 | |
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| 0.0482 | 16.0 | 7024 | 0.0107 | 0.998 | |
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| 0.0482 | 17.0 | 7463 | 0.0060 | 0.996 | |
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| 0.0418 | 18.0 | 7902 | 0.0037 | 0.998 | |
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| 0.0289 | 19.0 | 8341 | 0.0031 | 0.998 | |
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| 0.0242 | 20.0 | 8780 | 0.0029 | 0.998 | |
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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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