---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-amazon-shoe-reviews-scaled
  results: []
---

<!-- 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-amazon-shoe-reviews-scaled

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: 1.1836
- Accuracy: 0.456
- F1: [0.56281407 0.31088083 0.32608696 0.32142857 0.6640625 ]
- Precision: [0.5045045  0.34090909 0.37037037 0.35064935 0.59440559]
- Recall: [0.63636364 0.28571429 0.29126214 0.2967033  0.75221239]

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1                                                       | Precision                                                | Recall                                                   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
| 1.3447        | 1.0   | 141  | 1.1836          | 0.456    | [0.56281407 0.31088083 0.32608696 0.32142857 0.6640625 ] | [0.5045045  0.34090909 0.37037037 0.35064935 0.59440559] | [0.63636364 0.28571429 0.29126214 0.2967033  0.75221239] |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3