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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_sst2_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: sst2
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split: validation
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args: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9541284403669725
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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_sst2_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: 0.3623
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- Accuracy: 0.9541
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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: 256
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- eval_batch_size: 256
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- seed: 0
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 512
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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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| 0.2263 | 0.38 | 50 | 0.1874 | 0.9404 |
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| 0.1549 | 0.76 | 100 | 0.1661 | 0.9438 |
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| 0.1321 | 1.14 | 150 | 0.3832 | 0.9484 |
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| 0.1153 | 1.52 | 200 | 0.2551 | 0.9484 |
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| 0.1135 | 1.89 | 250 | 0.1375 | 0.9530 |
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| 0.0823 | 2.27 | 300 | 0.4848 | 0.9495 |
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| 0.1417 | 2.65 | 350 | 0.3618 | 0.9484 |
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| 0.0763 | 3.03 | 400 | 0.3594 | 0.9530 |
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| 0.0959 | 3.41 | 450 | 0.3692 | 0.9576 |
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| 0.0925 | 3.79 | 500 | 0.3623 | 0.9541 |
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| 0.1089 | 4.17 | 550 | 0.4750 | 0.9576 |
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| 0.0758 | 4.55 | 600 | 0.8276 | 0.9472 |
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| 0.0792 | 4.92 | 650 | 0.5894 | 0.9553 |
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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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