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mamlong34
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t5_small_race_mutlirc

Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
text-generation-inference
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update model card README.md

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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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- datasets:
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- - cosmos_qa
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  metrics:
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  - accuracy
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  model-index:
@@ -16,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # t5_small_race_mutlirc
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- This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cosmos_qa dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5929
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- - Accuracy: 0.4794
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  ## Model description
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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: 16
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  - seed: 42
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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: 50
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  - num_epochs: 3.0
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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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- | 0.7069 | 1.0 | 1250 | 0.6522 | 0.396 |
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- | 0.6595 | 2.0 | 2500 | 0.6009 | 0.4693 |
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- | 0.6374 | 3.0 | 3750 | 0.5929 | 0.4794 |
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  ### Framework versions
 
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
 
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  # t5_small_race_mutlirc
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5760
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+ - Accuracy: 0.5259
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 16
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  - seed: 42
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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: 1000
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  - num_epochs: 3.0
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:--------:|:---------------:|
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+ | 0.6043 | 1.0 | 14141 | 0.4832 | 0.5925 |
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+ | 0.5647 | 2.0 | 28282 | 0.5152 | 0.5659 |
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+ | 0.5237 | 3.0 | 42423 | 0.5760 | 0.5259 |
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  ### Framework versions