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--- |
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language: |
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- en |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: RTE |
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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: GLUE RTE |
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type: glue |
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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: 0.6931407942238267 |
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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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# RTE |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE RTE dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7698 |
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- Accuracy: 0.6931 |
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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: 32 |
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- eval_batch_size: 8 |
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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: 10.0 |
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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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| No log | 1.0 | 78 | 0.6982 | 0.4946 | |
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| No log | 2.0 | 156 | 0.6822 | 0.5632 | |
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| No log | 3.0 | 234 | 0.6642 | 0.5921 | |
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| No log | 4.0 | 312 | 0.6545 | 0.6101 | |
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| No log | 5.0 | 390 | 0.6433 | 0.6390 | |
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| No log | 6.0 | 468 | 0.6844 | 0.6606 | |
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| 0.5942 | 7.0 | 546 | 0.7054 | 0.6462 | |
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| 0.5942 | 8.0 | 624 | 0.7449 | 0.6643 | |
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| 0.5942 | 9.0 | 702 | 0.7662 | 0.6715 | |
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| 0.5942 | 10.0 | 780 | 0.7698 | 0.6931 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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