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

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: 0.9526
- Accuracy: 0.5793
- F1: [0.63065766 0.46287992 0.50875894 0.55936944 0.73581605]
- Precision: [0.62955567 0.46589769 0.49282983 0.58949625 0.7198044 ]
- Recall: [0.63176353 0.45990099 0.52575217 0.53217223 0.75255624]

## 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                                                   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
| 0.9618        | 1.0   | 2813 | 0.9526          | 0.5793   | [0.63065766 0.46287992 0.50875894 0.55936944 0.73581605] | [0.62955567 0.46589769 0.49282983 0.58949625 0.7198044 ] | [0.63176353 0.45990099 0.52575217 0.53217223 0.75255624] |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3