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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_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: 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: 0.0 |
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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_cola_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: 4.9143 |
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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: 32 |
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- eval_batch_size: 64 |
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- seed: 1 |
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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: 6 |
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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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| 0.5646 | 0.09 | 25 | 0.6556 | 0.6913 | |
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| 0.6392 | 0.19 | 50 | 0.5933 | 0.6913 | |
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| 0.5668 | 0.28 | 75 | 0.5673 | 0.6913 | |
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| 0.4777 | 0.37 | 100 | 0.5130 | 0.7872 | |
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| 0.4982 | 0.47 | 125 | 0.5462 | 0.7987 | |
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| 0.515 | 0.56 | 150 | 0.4918 | 0.8025 | |
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| 0.5279 | 0.65 | 175 | 0.4923 | 0.7900 | |
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| 0.4246 | 0.75 | 200 | 0.5310 | 0.7958 | |
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| 0.4437 | 0.84 | 225 | 0.4455 | 0.8159 | |
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| 0.4251 | 0.93 | 250 | 0.4847 | 0.8111 | |
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| 0.2875 | 1.03 | 275 | 0.5152 | 0.8102 | |
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| 0.3736 | 1.12 | 300 | 0.5038 | 0.8130 | |
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| 0.3489 | 1.21 | 325 | 0.4612 | 0.8159 | |
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| 0.3729 | 1.31 | 350 | 0.5098 | 0.8102 | |
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| 0.3574 | 1.4 | 375 | 0.5389 | 0.8121 | |
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| 0.3897 | 1.49 | 400 | 0.4788 | 0.8130 | |
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| 0.3785 | 1.59 | 425 | 0.4827 | 0.8150 | |
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| 0.4429 | 1.68 | 450 | 0.5501 | 0.8063 | |
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| 0.3893 | 1.77 | 475 | 0.4393 | 0.8245 | |
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| 0.3531 | 1.87 | 500 | 0.4769 | 0.8255 | |
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| 0.3853 | 1.96 | 525 | 0.4711 | 0.8284 | |
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| 0.3173 | 2.05 | 550 | 0.5262 | 0.8226 | |
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| 0.3102 | 2.15 | 575 | 0.5084 | 0.8284 | |
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| 0.3236 | 2.24 | 600 | 0.5517 | 0.8293 | |
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| 0.2618 | 2.33 | 625 | 0.5825 | 0.8322 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.11.6 |
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