| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: amazon_review_classification |
| results: [] |
| widget: |
| - 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" |
| output: |
| - label: Not Recommended |
| score: 0.783 |
| - label: Negative Experience |
| score: 0.087 |
| - label: Low Quality |
| score: 0.040 |
| - label: Poor Service |
| score: 0.026 |
| - label: Overpriced |
| score: 0.021 |
| - label: Positive Experience |
| score: 0.015 |
| - label: Excellent Service |
| score: 0.009 |
| - label: Great Value |
| score: 0.007 |
| - label: Highly Recommended |
| score: 0.006 |
| - label: High Quality |
| score: 0.005 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # amazon_review_classification |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.3976 |
| - Accuracy: 0.6732 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 115 | 1.0703 | 0.6732 | |
| | No log | 2.0 | 230 | 1.2393 | 0.6341 | |
| | No log | 3.0 | 345 | 1.1084 | 0.6683 | |
| | No log | 4.0 | 460 | 1.1262 | 0.6829 | |
| | 0.3201 | 5.0 | 575 | 1.3179 | 0.6732 | |
| | 0.3201 | 6.0 | 690 | 1.3832 | 0.6585 | |
| | 0.3201 | 7.0 | 805 | 1.2997 | 0.6683 | |
| | 0.3201 | 8.0 | 920 | 1.3872 | 0.6634 | |
| | 0.0863 | 9.0 | 1035 | 1.3832 | 0.6634 | |
| | 0.0863 | 10.0 | 1150 | 1.3976 | 0.6732 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
|
|
| ### Usage |
|
|
| ```python |
| from transformers import pipeline |
| |
| classifier = pipeline("sentiment-analysis", model="eren23/amazon_review_classification") |
| classifier(text) |
| ``` |
|
|
