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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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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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datasets: |
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- amazon_us_reviews |
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model-index: |
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- name: distilbert-amazon-shoe-reviews |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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type: amazon_us_reviews |
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name: Amazon US reviews |
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split: Shoes |
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metrics: |
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- type: accuracy |
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value: 0.6819221967963387 |
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name: Accuracy |
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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-amazon-shoe-reviews |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9536 |
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- Accuracy: 0.5767 |
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- F1: [0.62380713 0.45806452 0.5077951 0.56106774 0.73541247] |
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- Precision: [0.62537764 0.45920398 0.49326923 0.58508403 0.72376238] |
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- Recall: [0.62224449 0.45693069 0.52320245 0.53894533 0.74744376] |
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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: 32 |
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- eval_batch_size: 64 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:| |
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| 0.9704 | 1.0 | 2813 | 0.9536 | 0.5767 | [0.62380713 0.45806452 0.5077951 0.56106774 0.73541247] | [0.62537764 0.45920398 0.49326923 0.58508403 0.72376238] | [0.62224449 0.45693069 0.52320245 0.53894533 0.74744376] | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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