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---
license: apache-2.0
datasets:
- McAuley-Lab/Amazon-Reviews-2023
language:
- en
metrics:
- accuracy
base_model:
- microsoft/deberta-v3-base
pipeline_tag: text-classification
widget:
- text: The product didn't arrive on time and was damaged.
library_name: transformers
safetensors: true
---
### Training Details
The model was trained on the McAuley-Lab/Amazon-Reviews-2023 dataset. This dataset contains labeled customer reviews from Amazon, focusing on two primary categories: Positive and Negative.
### Training Hyperparameters
* Model: microsoft/deberta-v3-base
* Learning Rate: 3e-5
* Epochs: 6
* Train Batch Size: 16
* Gradient Accumulation Steps: 2
* Weight Decay: 0.015
* Warm-up Ratio: 0.1
### Evaluation
The model was evaluated using a subset of the Amazon reviews dataset, focusing on the binary classification of text as either positive or negative.
### Metrics
Accuracy: 0.98
Precision: 0.98
Recall: 0.99
F1-Score: 0.98 |