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README.md ADDED
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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: 0.7526366251198466
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+ ---
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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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+
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+ # t5-base_cola_dense_mare_mlp_einsum
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+
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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: 0.6369
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+ - Accuracy: 0.7526
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5857 | 0.19 | 50 | 0.6136 | 0.6913 |
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+ | 0.5918 | 0.37 | 100 | 0.6222 | 0.6913 |
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+ | 0.5688 | 0.56 | 150 | 0.6246 | 0.6913 |
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+ | 0.685 | 0.75 | 200 | 0.6150 | 0.6913 |
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+ | 0.565 | 0.93 | 250 | 0.6197 | 0.6913 |
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+ | 0.5892 | 1.12 | 300 | 0.6066 | 0.6922 |
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+ | 0.5444 | 1.31 | 350 | 0.5988 | 0.7009 |
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+ | 0.6097 | 1.5 | 400 | 0.5796 | 0.7076 |
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+ | 0.5904 | 1.68 | 450 | 0.5916 | 0.6884 |
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+ | 0.5898 | 1.87 | 500 | 0.5815 | 0.7057 |
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+ | 0.5569 | 2.06 | 550 | 0.5771 | 0.6999 |
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+ | 0.4553 | 2.24 | 600 | 0.6217 | 0.7210 |
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+ | 0.4796 | 2.43 | 650 | 0.6323 | 0.7229 |
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+ | 0.5362 | 2.62 | 700 | 0.6491 | 0.7229 |
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+ | 0.5756 | 2.8 | 750 | 0.5745 | 0.7018 |
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+ | 0.5731 | 2.99 | 800 | 0.6104 | 0.7315 |
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+ | 0.4573 | 3.18 | 850 | 0.6087 | 0.7248 |
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+ | 0.5395 | 3.36 | 900 | 0.6768 | 0.7459 |
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+ | 0.4447 | 3.55 | 950 | 0.6372 | 0.7383 |
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+ | 0.3891 | 3.74 | 1000 | 0.6589 | 0.7402 |
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+ | 0.3923 | 3.93 | 1050 | 0.6273 | 0.7344 |
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+ | 0.3855 | 4.11 | 1100 | 0.7189 | 0.7344 |
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+ | 0.4015 | 4.3 | 1150 | 0.6456 | 0.7469 |
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+ | 0.33 | 4.49 | 1200 | 0.7179 | 0.7450 |
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+ | 0.354 | 4.67 | 1250 | 0.6369 | 0.7526 |
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+
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+
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+ ### Framework versions
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+
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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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