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update model card README.md
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README.md
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---
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license: apache-2.0
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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: Finetuned_FLAN-T5_VALUE_adapterfusion_lr5e-4_bs32
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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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# Finetuned_FLAN-T5_VALUE_adapterfusion_lr5e-4_bs32
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This model is a fine-tuned version of [liuyanchen1015/FLAN-T5_GLUE_finetuning_lr3e-4](https://huggingface.co/liuyanchen1015/FLAN-T5_GLUE_finetuning_lr3e-4) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0870
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- Accuracy: 0.8692
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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: 42
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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: 3.0
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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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| 0.0862 | 0.08 | 2500 | 0.1059 | 0.8526 |
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| 0.092 | 0.17 | 5000 | 0.1025 | 0.856 |
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| 0.0943 | 0.25 | 7500 | 0.1126 | 0.8516 |
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| 0.0899 | 0.34 | 10000 | 0.0955 | 0.8578 |
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| 0.0896 | 0.42 | 12500 | 0.1046 | 0.8564 |
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| 0.0952 | 0.51 | 15000 | 0.0978 | 0.851 |
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| 0.0901 | 0.59 | 17500 | 0.0958 | 0.8498 |
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| 0.095 | 0.68 | 20000 | 0.0974 | 0.8532 |
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| 0.0955 | 0.76 | 22500 | 0.0982 | 0.853 |
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| 0.0912 | 0.85 | 25000 | 0.0980 | 0.853 |
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| 0.0913 | 0.93 | 27500 | 0.0944 | 0.8528 |
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| 0.0889 | 1.02 | 30000 | 0.0907 | 0.8592 |
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| 0.0871 | 1.1 | 32500 | 0.0933 | 0.855 |
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| 0.0872 | 1.18 | 35000 | 0.0904 | 0.861 |
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| 0.0859 | 1.27 | 37500 | 0.0879 | 0.8594 |
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| 0.0847 | 1.35 | 40000 | 0.0950 | 0.8584 |
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| 0.0827 | 1.44 | 42500 | 0.0909 | 0.8622 |
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| 0.0836 | 1.52 | 45000 | 0.0933 | 0.8552 |
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| 0.0805 | 1.61 | 47500 | 0.0928 | 0.8646 |
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| 0.0799 | 1.69 | 50000 | 0.0905 | 0.8648 |
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| 0.0789 | 1.78 | 52500 | 0.0863 | 0.87 |
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| 0.0786 | 1.86 | 55000 | 0.0907 | 0.8612 |
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| 0.0772 | 1.95 | 57500 | 0.0883 | 0.8672 |
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| 0.075 | 2.03 | 60000 | 0.0886 | 0.8664 |
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| 0.0727 | 2.12 | 62500 | 0.0878 | 0.8688 |
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| 0.0724 | 2.2 | 65000 | 0.0881 | 0.8708 |
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| 0.0729 | 2.28 | 67500 | 0.0879 | 0.8664 |
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| 0.0714 | 2.37 | 70000 | 0.0883 | 0.8694 |
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| 0.0694 | 2.45 | 72500 | 0.0876 | 0.8724 |
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| 0.0698 | 2.54 | 75000 | 0.0869 | 0.8698 |
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| 0.0706 | 2.62 | 77500 | 0.0872 | 0.8712 |
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| 0.0685 | 2.71 | 80000 | 0.0874 | 0.8692 |
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| 0.068 | 2.79 | 82500 | 0.0873 | 0.869 |
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| 0.0685 | 2.88 | 85000 | 0.0863 | 0.8688 |
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| 0.068 | 2.96 | 87500 | 0.0870 | 0.8692 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.0+cu117
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- Datasets 2.10.1
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- Tokenizers 0.12.1
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