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--- |
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license: apache-2.0 |
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base_model: t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- super_glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: superglue_rte-t5-base |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: super_glue |
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type: super_glue |
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config: rte |
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split: validation |
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args: rte |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8405797101449275 |
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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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# superglue_rte-t5-base |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the super_glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8826 |
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- Accuracy: 0.8406 |
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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: 5e-05 |
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- train_batch_size: 4 |
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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: 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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| 0.7037 | 1.0 | 623 | 0.6646 | 0.5797 | |
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| 0.6448 | 2.0 | 1246 | 0.5461 | 0.7899 | |
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| 0.4943 | 3.0 | 1869 | 0.8069 | 0.7536 | |
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| 0.3854 | 4.0 | 2492 | 1.2553 | 0.8188 | |
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| 0.1244 | 5.0 | 3115 | 1.4887 | 0.7826 | |
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| 0.0836 | 6.0 | 3738 | 1.7422 | 0.7681 | |
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| 0.0672 | 7.0 | 4361 | 1.7002 | 0.8116 | |
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| 0.0449 | 8.0 | 4984 | 1.9237 | 0.7971 | |
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| 0.0246 | 9.0 | 5607 | 1.7064 | 0.7899 | |
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| 0.0239 | 10.0 | 6230 | 1.4433 | 0.8551 | |
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| 0.0233 | 11.0 | 6853 | 2.1623 | 0.7754 | |
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| 0.0348 | 12.0 | 7476 | 2.2059 | 0.7754 | |
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| 0.0268 | 13.0 | 8099 | 1.9322 | 0.8261 | |
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| 0.0076 | 14.0 | 8722 | 2.5687 | 0.7464 | |
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| 0.0117 | 15.0 | 9345 | 2.3024 | 0.7899 | |
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| 0.0129 | 16.0 | 9968 | 2.0848 | 0.7971 | |
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| 0.0206 | 17.0 | 10591 | 1.9453 | 0.8333 | |
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| 0.0162 | 18.0 | 11214 | 2.1232 | 0.7971 | |
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| 0.0132 | 19.0 | 11837 | 1.9754 | 0.8406 | |
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| 0.0098 | 20.0 | 12460 | 1.8826 | 0.8406 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.13.3 |
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