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--- |
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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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- yelp_polarity |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased-finetuned-yelp-polarity |
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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_polarity |
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type: yelp_polarity |
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config: plain_text |
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split: train |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9617414248021108 |
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- name: F1 |
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type: f1 |
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value: 0.9617407987866946 |
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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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# distilbert-base-uncased-finetuned-yelp-polarity |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yelp_polarity dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1395 |
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- Accuracy: 0.9617 |
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- F1: 0.9617 |
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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: 24 |
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- eval_batch_size: 24 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.1334 | 1.0 | 2332 | 0.1141 | 0.9602 | 0.9602 | |
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| 0.0722 | 2.0 | 4664 | 0.1395 | 0.9617 | 0.9617 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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