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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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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: t5-base_rte_dense_sp0_ar0 |
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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 |
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type: 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: 0.0 |
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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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# t5-base_rte_dense_sp0_ar0 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9086 |
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- Accuracy: 0.0 |
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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: 8 |
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- eval_batch_size: 16 |
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- seed: 1 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 20 |
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- num_epochs: 5 |
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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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| 0.6787 | 0.16 | 25 | 0.6850 | 0.5307 | |
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| 0.7034 | 0.32 | 50 | 0.6689 | 0.5704 | |
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| 0.6478 | 0.48 | 75 | 0.6356 | 0.6570 | |
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| 0.6889 | 0.64 | 100 | 0.6188 | 0.6859 | |
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| 0.588 | 0.8 | 125 | 0.5892 | 0.6859 | |
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| 0.5989 | 0.96 | 150 | 0.6802 | 0.6606 | |
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| 0.5392 | 1.12 | 175 | 0.5836 | 0.7329 | |
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| 0.5497 | 1.28 | 200 | 0.6758 | 0.6715 | |
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| 0.5567 | 1.44 | 225 | 0.7056 | 0.6643 | |
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| 0.5063 | 1.6 | 250 | 0.5617 | 0.7401 | |
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| 0.5644 | 1.76 | 275 | 0.5737 | 0.7256 | |
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| 0.6018 | 1.92 | 300 | 0.6179 | 0.7112 | |
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| 0.4554 | 2.08 | 325 | 0.5339 | 0.7509 | |
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| 0.3778 | 2.24 | 350 | 0.5495 | 0.7726 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.9.0 |
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- Tokenizers 0.14.1 |
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