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README.md
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---
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license: apache-2.0
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base_model: t5-large
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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-large_cola_dense_epochs-5
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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: 0.837967401725791
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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-large_cola_dense_epochs-5
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This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9474
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- Accuracy: 0.8380
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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: 32
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- seed: 0
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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: 20
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- num_epochs: 5
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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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| 0.4193 | 0.37 | 50 | 0.6334 | 0.7996 |
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| 0.3251 | 0.75 | 100 | 0.5550 | 0.8092 |
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| 0.2903 | 1.12 | 150 | 0.5062 | 0.8255 |
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| 0.2551 | 1.49 | 200 | 0.4837 | 0.8341 |
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| 0.2893 | 1.87 | 250 | 0.4571 | 0.8360 |
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| 0.175 | 2.24 | 300 | 1.0091 | 0.8351 |
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| 0.17 | 2.61 | 350 | 0.6112 | 0.8418 |
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| 0.1838 | 2.99 | 400 | 0.5199 | 0.8389 |
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| 0.1342 | 3.36 | 450 | 1.7694 | 0.8408 |
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| 0.1458 | 3.73 | 500 | 1.9474 | 0.8380 |
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| 0.0828 | 4.1 | 550 | 1.6033 | 0.8428 |
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| 0.096 | 4.48 | 600 | 1.9796 | 0.8418 |
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| 0.2999 | 4.85 | 650 | 1.7943 | 0.8456 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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