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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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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- name: amazon_review_classification |
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results: [] |
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widget: |
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- text: "Title: These earrings are much smaller than pictured. They are so tiny \n Text: The online picture is deceiving. They are shown much larger than their actual size. Was very disappointed" |
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output: |
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- label: Not Recommended |
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score: 0.783 |
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- label: Negative Experience |
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score: 0.087 |
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- label: Low Quality |
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score: 0.040 |
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- label: Poor Service |
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score: 0.026 |
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- label: Overpriced |
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score: 0.021 |
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- label: Positive Experience |
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score: 0.015 |
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- label: Excellent Service |
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score: 0.009 |
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- label: Great Value |
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score: 0.007 |
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- label: Highly Recommended |
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score: 0.006 |
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- label: High Quality |
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score: 0.005 |
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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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# amazon_review_classification |
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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: 1.3976 |
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- Accuracy: 0.6732 |
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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: linear |
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- num_epochs: 10 |
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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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| No log | 1.0 | 115 | 1.0703 | 0.6732 | |
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| No log | 2.0 | 230 | 1.2393 | 0.6341 | |
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| No log | 3.0 | 345 | 1.1084 | 0.6683 | |
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| No log | 4.0 | 460 | 1.1262 | 0.6829 | |
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| 0.3201 | 5.0 | 575 | 1.3179 | 0.6732 | |
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| 0.3201 | 6.0 | 690 | 1.3832 | 0.6585 | |
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| 0.3201 | 7.0 | 805 | 1.2997 | 0.6683 | |
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| 0.3201 | 8.0 | 920 | 1.3872 | 0.6634 | |
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| 0.0863 | 9.0 | 1035 | 1.3832 | 0.6634 | |
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| 0.0863 | 10.0 | 1150 | 1.3976 | 0.6732 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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### Usage |
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```python |
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from transformers import pipeline |
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classifier = pipeline("sentiment-analysis", model="eren23/amazon_review_classification") |
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classifier(text) |
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``` |
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