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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_cola_dense |
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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: cola |
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split: validation |
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args: cola |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6912751677852349 |
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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_cola_dense |
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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: 0.6351 |
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- Accuracy: 0.6913 |
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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: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 200 |
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- num_epochs: 1 |
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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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| 0.6331 | 0.07 | 10 | 0.6263 | 0.6855 | |
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| 0.626 | 0.15 | 20 | 0.6247 | 0.6826 | |
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| 0.6412 | 0.22 | 30 | 0.6240 | 0.6865 | |
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| 0.6497 | 0.3 | 40 | 0.6210 | 0.6874 | |
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| 0.6226 | 0.37 | 50 | 0.6213 | 0.6874 | |
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| 0.6183 | 0.45 | 60 | 0.6198 | 0.6894 | |
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| 0.6034 | 0.52 | 70 | 0.6202 | 0.6894 | |
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| 0.5802 | 0.6 | 80 | 0.6219 | 0.6913 | |
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| 0.6005 | 0.67 | 90 | 0.6261 | 0.6913 | |
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| 0.6178 | 0.75 | 100 | 0.6331 | 0.6922 | |
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| 0.5887 | 0.82 | 110 | 0.6344 | 0.6913 | |
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| 0.6492 | 0.9 | 120 | 0.6371 | 0.6913 | |
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| 0.6333 | 0.97 | 130 | 0.6376 | 0.6913 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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