---
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: 0.9546
- Accuracy: 0.5788
- F1: [0.62939855 0.4656164  0.50839092 0.5594581  0.73356926]
- Precision: [0.62705122 0.47043962 0.49258728 0.58103179 0.7255    ]
- Recall: [0.63176353 0.46089109 0.52524222 0.53942912 0.74182004]

## 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                                                   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
| 0.9611        | 1.0   | 2813 | 0.9546          | 0.5788   | [0.62939855 0.4656164  0.50839092 0.5594581  0.73356926] | [0.62705122 0.47043962 0.49258728 0.58103179 0.7255    ] | [0.63176353 0.46089109 0.52524222 0.53942912 0.74182004] |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3