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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tau/commonsense_qa |
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metrics: |
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- accuracy |
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model_index: |
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- name: aristo-roberta-finetuned-csqa |
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results: |
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- dataset: |
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name: commonsense_qa |
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type: commonsense_qa |
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args: default |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.7305487394332886 |
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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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# aristo-roberta-finetuned-csqa |
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This model is a fine-tuned version of [LIAMF-USP/aristo-roberta](https://huggingface.co/LIAMF-USP/aristo-roberta) on the commonsense_qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2187 |
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- Accuracy: 0.7305 |
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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: 1e-05 |
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- train_batch_size: 16 |
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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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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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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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| 1.131 | 1.0 | 609 | 0.7109 | 0.7232 | |
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| 0.6957 | 2.0 | 1218 | 0.6912 | 0.7346 | |
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| 0.459 | 3.0 | 1827 | 0.8364 | 0.7305 | |
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| 0.3063 | 4.0 | 2436 | 1.0595 | 0.7322 | |
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| 0.2283 | 5.0 | 3045 | 1.2187 | 0.7305 | |
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### Framework versions |
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- Transformers 4.9.0 |
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- Pytorch 1.9.0 |
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- Datasets 1.10.2 |
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- Tokenizers 0.10.3 |
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