| | --- |
| | license: apache-2.0 |
| | base_model: t5-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - glue |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: t5-base_cola_dense |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: glue |
| | type: glue |
| | config: cola |
| | split: validation |
| | args: cola |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6912751677852349 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # t5-base_cola_dense |
| |
|
| | This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6351 |
| | - Accuracy: 0.6913 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 200 |
| | - num_epochs: 1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.6331 | 0.07 | 10 | 0.6263 | 0.6855 | |
| | | 0.626 | 0.15 | 20 | 0.6247 | 0.6826 | |
| | | 0.6412 | 0.22 | 30 | 0.6240 | 0.6865 | |
| | | 0.6497 | 0.3 | 40 | 0.6210 | 0.6874 | |
| | | 0.6226 | 0.37 | 50 | 0.6213 | 0.6874 | |
| | | 0.6183 | 0.45 | 60 | 0.6198 | 0.6894 | |
| | | 0.6034 | 0.52 | 70 | 0.6202 | 0.6894 | |
| | | 0.5802 | 0.6 | 80 | 0.6219 | 0.6913 | |
| | | 0.6005 | 0.67 | 90 | 0.6261 | 0.6913 | |
| | | 0.6178 | 0.75 | 100 | 0.6331 | 0.6922 | |
| | | 0.5887 | 0.82 | 110 | 0.6344 | 0.6913 | |
| | | 0.6492 | 0.9 | 120 | 0.6371 | 0.6913 | |
| | | 0.6333 | 0.97 | 130 | 0.6376 | 0.6913 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
