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kennethge123
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superglue_rte-t5-base

Text Classification
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
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README.md ADDED
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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: 0.7725631768953068
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+ ---
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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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+
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+ # superglue_rte-t5-base
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+
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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: 2.5687
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+ - Accuracy: 0.7726
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.7109 | 1.0 | 623 | 0.6765 | 0.5740 |
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+ | 0.6562 | 2.0 | 1246 | 0.6030 | 0.6968 |
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+ | 0.548 | 3.0 | 1869 | 0.8049 | 0.7617 |
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+ | 0.4129 | 4.0 | 2492 | 1.3536 | 0.7329 |
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+ | 0.2189 | 5.0 | 3115 | 1.3886 | 0.7834 |
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+ | 0.1378 | 6.0 | 3738 | 1.7001 | 0.7690 |
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+ | 0.0905 | 7.0 | 4361 | 2.0587 | 0.7545 |
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+ | 0.0434 | 8.0 | 4984 | 2.1796 | 0.7798 |
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+ | 0.0715 | 9.0 | 5607 | 1.9936 | 0.7978 |
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+ | 0.0616 | 10.0 | 6230 | 1.9794 | 0.7762 |
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+ | 0.0609 | 11.0 | 6853 | 2.5575 | 0.7509 |
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+ | 0.0108 | 12.0 | 7476 | 2.1022 | 0.7834 |
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+ | 0.0142 | 13.0 | 8099 | 2.0628 | 0.7834 |
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+ | 0.03 | 14.0 | 8722 | 2.1540 | 0.7726 |
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+ | 0.0163 | 15.0 | 9345 | 2.3830 | 0.7653 |
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+ | 0.0152 | 16.0 | 9968 | 2.5031 | 0.7617 |
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+ | 0.0092 | 17.0 | 10591 | 2.4850 | 0.7653 |
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+ | 0.0069 | 18.0 | 11214 | 2.4939 | 0.7726 |
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+ | 0.0184 | 19.0 | 11837 | 2.4949 | 0.7690 |
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+ | 0.0204 | 20.0 | 12460 | 2.5687 | 0.7726 |
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+
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+
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+ ### Framework versions
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+
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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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