---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-cased-reviews-v1
  results: []
widget:
- text: >-
    Red Hot Chili Peppers on vinyl has been a disappointing experience.. I had
    to return both “By The Way” and “Stadium Arcadium” because there were skips
    on almost all of it.. Kind of made it seem like the record label just went
    cheap, which is a disservice to anyone that actually listens to their
    vinyl...This “Greatest Hits” compilation did not have the same problems as
    the other two I bought. It sounded as it should have, and there were no
    skips.
datasets:
- yyu/amazon-attrprompt
language:
- en
---

<!-- 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-cased-reviews-v1

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on yyu/amazon-attrprompt dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9022
- Accuracy: {'accuracy': 0.7478260869565218}
- F1 Score: {'f1': 0.7350319489971969}

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1 Score                   |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
| 0.2514        | 1.0   | 1728 | 1.8422          | {'accuracy': 0.7347826086956522} | {'f1': 0.7217427746565059} |
| 0.2709        | 2.0   | 3456 | 1.8755          | {'accuracy': 0.7347826086956522} | {'f1': 0.7200496580345588} |
| 0.0912        | 3.0   | 5184 | 1.9022          | {'accuracy': 0.7478260869565218} | {'f1': 0.7350319489971969} |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0