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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ecommerce_reviews_with_language_drift
metrics:
- accuracy
- f1
model-index:
- name: distilbert_reviews_with_language_drift
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ecommerce_reviews_with_language_drift
type: ecommerce_reviews_with_language_drift
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.818
- name: F1
type: f1
value: 0.8167126877417763
widget:
- text: "Poor quality of fabric and ridiculously tight at chest. It's way too short."
example_title: "Negative"
- text: "One worked perfectly, but the other one has a slight leak and we end up with water underneath the filter."
example_title: "Neutral"
- text: "I liked the price most! Nothing to dislike here!"
example_title: "Positive"
---
<!-- 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. -->
# distilbert_reviews_with_language_drift
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ecommerce_reviews_with_language_drift dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4970
- Accuracy: 0.818
- F1: 0.8167
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.593 | 1.0 | 500 | 0.4723 | 0.799 | 0.7976 |
| 0.3714 | 2.0 | 1000 | 0.4679 | 0.818 | 0.8177 |
| 0.2652 | 3.0 | 1500 | 0.4970 | 0.818 | 0.8167 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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