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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- yelp_review_full |
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metrics: |
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- accuracy |
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model-index: |
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- name: yelp_review_rating_reberta_base |
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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: yelp_review_full |
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type: yelp_review_full |
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config: yelp_review_full |
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split: train |
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args: yelp_review_full |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.67086 |
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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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# yelp_review_rating_reberta_base |
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This model was trained from scratch on the yelp_review_full dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8071 |
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- Accuracy: 0.6709 |
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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: 2e-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: cosine |
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- num_epochs: 6 |
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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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| 0.8355 | 1.0 | 40625 | 0.6449 | 0.8211 | |
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| 0.7709 | 2.0 | 81250 | 0.6615 | 0.7877 | |
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| 0.7141 | 3.0 | 121875 | 0.6712 | 0.7689 | |
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| 0.6511 | 4.0 | 162500 | 0.6724 | 0.7845 | |
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| 0.6229 | 5.0 | 203125 | 0.6719 | 0.8009 | |
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| 0.6036 | 6.0 | 243750 | 0.8071 | 0.6709 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.6.1 |
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- Tokenizers 0.12.1 |
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