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--- |
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license: apache-2.0 |
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base_model: lukeleeai/t5-base_cola_densedense_baseline |
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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_mare_mlp_einsum |
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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: 0.7516778523489933 |
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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_mare_mlp_einsum |
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This model is a fine-tuned version of [lukeleeai/t5-base_cola_densedense_baseline](https://huggingface.co/lukeleeai/t5-base_cola_densedense_baseline) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7682 |
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- Accuracy: 0.7517 |
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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: 32 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- total_eval_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: 20 |
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- num_epochs: 8 |
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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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| 0.5856 | 0.19 | 50 | 0.6260 | 0.6913 | |
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| 0.5836 | 0.37 | 100 | 0.6029 | 0.6913 | |
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| 0.5724 | 0.56 | 150 | 0.6055 | 0.6932 | |
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| 0.6635 | 0.75 | 200 | 0.6171 | 0.6922 | |
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| 0.5634 | 0.93 | 250 | 0.6162 | 0.6999 | |
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| 0.5361 | 1.12 | 300 | 0.6142 | 0.6932 | |
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| 0.5426 | 1.31 | 350 | 0.5920 | 0.7057 | |
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| 0.6255 | 1.5 | 400 | 0.5884 | 0.7095 | |
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| 0.6312 | 1.68 | 450 | 0.5723 | 0.7095 | |
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| 0.5686 | 1.87 | 500 | 0.5894 | 0.7057 | |
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| 0.5486 | 2.06 | 550 | 0.5590 | 0.7124 | |
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| 0.4436 | 2.24 | 600 | 0.5838 | 0.7220 | |
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| 0.4405 | 2.43 | 650 | 0.6176 | 0.7315 | |
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| 0.4785 | 2.62 | 700 | 0.6236 | 0.7296 | |
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| 0.5759 | 2.8 | 750 | 0.6233 | 0.7191 | |
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| 0.6156 | 2.99 | 800 | 0.6807 | 0.7392 | |
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| 0.4843 | 3.18 | 850 | 0.6337 | 0.7373 | |
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| 0.5408 | 3.36 | 900 | 0.7107 | 0.7392 | |
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| 0.4327 | 3.55 | 950 | 0.6256 | 0.7239 | |
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| 0.4318 | 3.74 | 1000 | 0.6951 | 0.7478 | |
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| 0.4047 | 3.93 | 1050 | 0.6566 | 0.7430 | |
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| 0.423 | 4.11 | 1100 | 0.6731 | 0.7440 | |
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| 0.3919 | 4.3 | 1150 | 0.6750 | 0.7392 | |
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| 0.4041 | 4.49 | 1200 | 0.6464 | 0.7421 | |
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| 0.3941 | 4.67 | 1250 | 0.6580 | 0.7517 | |
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| 0.3834 | 4.86 | 1300 | 0.6257 | 0.7459 | |
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| 0.2678 | 5.05 | 1350 | 0.6464 | 0.7555 | |
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| 0.3202 | 5.23 | 1400 | 0.7048 | 0.7507 | |
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| 0.2869 | 5.42 | 1450 | 0.7405 | 0.7565 | |
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| 0.3359 | 5.61 | 1500 | 0.6393 | 0.7593 | |
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| 0.3528 | 5.79 | 1550 | 0.6249 | 0.7555 | |
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| 0.3304 | 5.98 | 1600 | 0.6349 | 0.7565 | |
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| 0.2862 | 6.17 | 1650 | 0.7497 | 0.7670 | |
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| 0.2315 | 6.36 | 1700 | 0.7787 | 0.7622 | |
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| 0.3251 | 6.54 | 1750 | 0.7038 | 0.7555 | |
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| 0.3584 | 6.73 | 1800 | 0.7732 | 0.7603 | |
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| 0.1804 | 6.92 | 1850 | 0.8226 | 0.7584 | |
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| 0.2264 | 7.1 | 1900 | 0.7420 | 0.7613 | |
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| 0.2374 | 7.29 | 1950 | 0.7825 | 0.7507 | |
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| 0.203 | 7.48 | 2000 | 0.7575 | 0.7641 | |
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| 0.238 | 7.66 | 2050 | 1.9945 | 0.7603 | |
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| 0.2328 | 7.85 | 2100 | 0.7682 | 0.7517 | |
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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 2.9.0 |
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- Tokenizers 0.11.6 |
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